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Vallet, B., and B. Lévy. "Spectral Geometry Processing with Manifold Harmonics." Computer Graphics Forum 27, no. 2 (2008): 251–60. http://dx.doi.org/10.1111/j.1467-8659.2008.01122.x.
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Fumero, Marco, Michael Möller, and Emanuele Rodolà. "Nonlinear spectral geometry processing via the TV transform." ACM Transactions on Graphics 39, no. 6 (2020): 1–16. http://dx.doi.org/10.1145/3414685.3417849.
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Clouet, Axel, Jérôme Vaillant, and David Alleysson. "The Geometry of Noise in Color and Spectral Image Sensors." Sensors 20, no. 16 (2020): 4487. http://dx.doi.org/10.3390/s20164487.
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Digital images are always affected by noise and the reduction of its impact is an active field of research. Noise due to random photon fall onto the sensor is unavoidable but could be amplified by the camera image processing such as in the color correction step. Color correction is expressed as the combination of a spectral estimation and a computation of color coordinates in a display color space. Then we use geometry to depict raw, spectral and color signals and noise. Geometry is calibrated on the physics of image acquisition and spectral characteristics of the sensor to study the impact of the sensor space metric on noise amplification. Since spectral channels are non-orthogonal, we introduce the contravariant signal to noise ratio for noise evaluation at spectral reconstruction level. Having definitions of signal to noise ratio for each steps of spectral or color reconstruction, we compare performances of different types of sensors (RGB, RGBW, RGBWir, CMY, RYB, RGBC).
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Kleinert, A., F. Friedl-Vallon, T. Guggenmoser, et al. "Level 0 to 1 processing of the imaging Fourier transform spectrometer GLORIA: generation of radiometrically and spectrally calibrated spectra." Atmospheric Measurement Techniques 7, no. 12 (2014): 4167–84. http://dx.doi.org/10.5194/amt-7-4167-2014.
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Abstract. The Gimballed Limb Observer for Radiance Imaging of the Atmosphere (GLORIA) is an imaging Fourier transform spectrometer that is capable of operating on various high-altitude research aircraft. It measures the atmospheric emission in the thermal infrared spectral region in limb and nadir geometry. GLORIA consists of a classical Michelson interferometer combined with an infrared camera. The infrared detector has a usable area of 128 × 128 pixels, measuring up to 16 384 interferograms simultaneously. Imaging Fourier transform spectrometers impose a number of challenges with respect to instrument calibration and algorithm development. The optical setup with extremely high optical throughput requires the development of new methods and algorithms for spectral and radiometric calibration. Due to the vast amount of data there is a high demand for scientifically intelligent optimisation of the data processing. This paper outlines the characterisation and processing steps required for the generation of radiometrically and spectrally calibrated spectra. Methods for performance optimisation of the processing algorithm are presented. The performance of the data processing and the quality of the calibrated spectra are demonstrated for measurements collected during the first deployments of GLORIA on aircraft.
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Kleinert, A., F. Friedl-Vallon, T. Guggenmoser, et al. "Level 0 to 1 processing of the imaging Fourier transform spectrometer GLORIA: generation of radiometrically and spectrally calibrated spectra." Atmospheric Measurement Techniques Discussions 7, no. 3 (2014): 2827–78. http://dx.doi.org/10.5194/amtd-7-2827-2014.
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Abstract. The Gimballed Limb Observer for Radiance Imaging of the Atmosphere (GLORIA) is an imaging Fourier transform spectrometer that is capable of operating on various high altitude research aircraft. It measures the atmospheric emission in the thermal infrared spectral region in limb and nadir geometry. GLORIA consists of a classical Michelson interferometer combined with an infrared camera. The infrared detector has a usable range of 128 × 128 pixels, measuring up to 16 384 interferograms simultaneously. Imaging Fourier transform spectrometers impose a number of challenges with respect to instrument calibration and algorithm development. The innovative optical setup with extremely high optical throughput requires the development of new methods and algorithms for spectral and radiometric calibration. Due to the vast amount of data there is a high demand for scientifically intelligent optimisation of the data processing. This paper outlines the characterisation and processing steps required for the generation of radiometrically and spectrally calibrated spectra. Methods for performance optimisation of the processing algorithm are presented. The performance of the data processing and the quality of the calibrated spectra are demonstrated for measurements collected during the first deployments of GLORIA on aircraft.
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Patané, Giuseppe. "STAR - Laplacian Spectral Kernels and Distances for Geometry Processing and Shape Analysis." Computer Graphics Forum 35, no. 2 (2016): 599–624. http://dx.doi.org/10.1111/cgf.12866.
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Litvinovich, Hl S., and I. I. Bruchkouski. "Algorithm for preliminary processing of charge coupled devices array data based on the adaptive Wiener filter." Informatics 18, no. 1 (2021): 72–83. http://dx.doi.org/10.37661/1816-0301-2021-18-1-72-83.
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The researcher should choose the modes of recording spectra which allow to achieve the highest accuracy of spectral measurements in remote sensing systems. When registering a signal from aircraft which provide maximum coverage of the studied area, it is important to obtain a signal with the maximum signal-to- noise ratio in a minimum time, since the accumulation of spectra samples for averaging is impossible. The paper presents the experimental results of determining the noise components (readout noise, photon, electronic shot, pattern noise) for a monochrome uncooled CCD-line detector Toshiba TCD1304DG (CCD – charge-coupled devices) with various conditions of spectrum registration: detector temperature, exposition. Obtained dependences of the noise components make it possible to estimate the noise level for well-known conditions of spectra registration. The algorithm for processing CCD data based on an adaptive Wiener filter is proposed to increase the signal-to-noise ratio by using a priori information about the statistical parameters of the noise components. Such approach has allowed to increase the signal-to-noise ratio of sky spectral brightness by 4–9 dB for exposure times. The practical application of the algorithm has reduced the uncertainty in the vegetation index NDVI by 1.5 times when recording the reflection spectra of vegetation from the aircraft in the nadir measurement geometry.
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Jiang, Yonghua, Jingyin Wang, Li Zhang, Guo Zhang, Xin Li, and Jiaqi Wu. "Geometric Processing and Accuracy Verification of Zhuhai-1 Hyperspectral Satellites." Remote Sensing 11, no. 9 (2019): 996. http://dx.doi.org/10.3390/rs11090996.
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The second batch of Zhuhai-1 microsatellites was successfully launched on 26 April 2018. The batch included four Orbita hyperspectral satellites (referred to as OHS-A, OHS-B, OHS-C, and OHS-D) and one video satellite (OVS-2A), which have excellent hyperspectral data acquisition abilities. For the first time in China, a number of hyperspectral satellite networks have been realized. To ensure the application of hyperspectral remote sensing data, a series of on-orbit geometry processing and accuracy verification studies has been carried out on the “Zhuhai-1” hyperspectral camera since the satellite was launched. This paper presents the geometric processing methods involved in the production of Zhuhai-1 hyperspectral satellite basic products, including geometric calibration and basic product production algorithms. The OHS images were used to perform on-orbit geometric calibration, and the calibration accuracy was better than 0.5 pixels. The registration accuracy of the image spectrum of the basic product after calibration, the single orientation accuracy, and the accuracy of the regional network adjustment were evaluated. The spectral registration accuracy of the OHS basic products is 0.3–0.5 pixels, which is equivalent to the spectral band calibration accuracy. The single orientation accuracy is better than 1.5 pixels and the regional network adjustment accuracy is better than 1.2 pixels. The generated area orthoimages meet the seamless edge requirements, which verifies that the OHS basic product image has good regional mapping capabilities and can meet the application requirements.
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Feng, Sheng, Xiaoqiang Hua, and Xiaoqian Zhu. "Matrix Information Geometry for Spectral-Based SPD Matrix Signal Detection with Dimensionality Reduction." Entropy 22, no. 9 (2020): 914. http://dx.doi.org/10.3390/e22090914.
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In this paper, a novel signal detector based on matrix information geometric dimensionality reduction (DR) is proposed, which is inspired from spectrogram processing. By short time Fourier transform (STFT), the received data are represented as a 2-D high-precision spectrogram, from which we can well judge whether the signal exists. Previous similar studies extracted insufficient information from these spectrograms, resulting in unsatisfactory detection performance especially for complex signal detection task at low signal-noise-ratio (SNR). To this end, we use a global descriptor to extract abundant features, then exploit the advantages of matrix information geometry technique by constructing the high-dimensional features as symmetric positive definite (SPD) matrices. In this case, our task for signal detection becomes a binary classification problem lying on an SPD manifold. Promoting the discrimination of heterogeneous samples through information geometric DR technique that is dedicated to SPD manifold, our proposed detector achieves satisfactory signal detection performance in low SNR cases using the K distribution simulation and the real-life sea clutter data, which can be widely used in the field of signal detection.
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Zolotov, Denis, Alexey Buzmakov, Maxim Grigoriev, and Igor Schelokov. "Dual-energy crystal-analyzer scheme for spectral tomography." Journal of Applied Crystallography 53, no. 3 (2020): 781–88. http://dx.doi.org/10.1107/s1600576720005439.
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In the present work, a method for adjusting a crystal analyzer to separate two characteristic lines from the spectrum of a conventional X-ray tube for simultaneous registration of tomographic projections is proposed. The experimental implementation of this method using radiation of a molybdenum anode (Kα1, Kβ lines) and a silicon Si(111) crystal analyzer in Laue geometry is presented. Projection images at different wavelengths are separated in space and can be recorded independently for further processing. Potential uses of this scheme are briefly discussed.
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Saiko, Guennadi, and Alexandre Douplik. "Reflectance of Biological Turbid Tissues under Wide Area Illumination: Single Backward Scattering Approach." International Journal of Photoenergy 2014 (2014): 1–8. http://dx.doi.org/10.1155/2014/241364.
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Various scenarios of light propagation paths in turbid media (single backward scattering, multiple backward scattering, banana shape) are discussed and their contributions to reflectance spectra are estimated. It has been found that a single backward or multiple forward scattering quasi-1D paths can be the major contributors to reflected spectra in wide area illumination scenario. Such a single backward scattering (SBS) approximation allows developing of an analytical approach which can take into account refractive index mismatched boundary conditions and multilayer geometry and can be used for real-time spectral processing. The SBS approach can be potentially applied for the distances between the transport and reduced scattering domains. Its validation versus the Kubelka-Munk model, path integrals, and diffusion approximation of the radiation transport theory is discussed.
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Singh, S., D. Dutta, U. Singh, J. R. Sharma, and V. K. Dadhwal. "Hydat-A Hyperspectral Data Processing Tool for Field Spectroradiometer Data." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-8 (November 28, 2014): 481–84. http://dx.doi.org/10.5194/isprsarchives-xl-8-481-2014.
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A hyperspectral data processing tool "HyDAT" has been developed in MATLAB environment for processing of Field Spectroradiometer data for vegetation studies. Several basic functions e.g. data visualization, pre-processing, noise removal and data transformation and features like automatic absorption feature recovery and their characterization have been introduced. A new concept of spectral geometry has been included as a separate module which is conceptualized as triangle formed over spectral space joining the vertices of green reflectance peak, red well and inflection point and is extremely useful for vegetation health analysis. A large variety of spectral indices both static and dynamic, have been introduced which is useful for remote estimation of foliar biochemicals. Keeping in view the computational requirement, MATLAB was used in the programming environment. It has various in-built functions for statistical and mathematical analysis, signal processing functions like FFT (Fast Fourier Transform), CWT (Continuous Wavelet Transform), direct smoothing function for moving average, Savitzky-Golay smoothing technique, etc. which can be used with ease for the signal processing and field data analysis. FSF (Field Spectroscopy Facility) Post processing Toolbox can also be freely downloaded and can be used for the direct importing and pre-processing of Spectroradiometer data for detector overlap correction, erroneous water band removal and smoothing. The complete package of the software has been bundled for standalone application of shared libraries with additional files for end users. The software is powered by creation of spectral library and customized report generation. An online help menu guides the user for performing different functions. The tool is capable of reducing the time required for processing field based hyperspectral data significantly and eliminate the need for different software to process the raw data and spectral features extraction.
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Cammarasana, Simone, and Giuseppe Patané. "Localised and shape-aware functions for spectral geometry processing and shape analysis: A survey & perspectives." Computers & Graphics 97 (June 2021): 1–18. http://dx.doi.org/10.1016/j.cag.2021.03.006.
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Pavlov, Dmitrii V., Aleksey P. Porfirev, Anton Dyshliuk, and Aleksandr A. Kuchmizhak. "Coaxial Aperture Arrays Produced by Ultrafast Direct Femtosecond Laser Processing with Spatially Multiplexed Cylindrical Vector Beams." Solid State Phenomena 312 (November 2020): 148–53. http://dx.doi.org/10.4028/www.scientific.net/ssp.312.148.
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Direct femtosecond laser printing was used to fabricate circular-and coaxial-shaped hole arrays at ultrafast printing rate up to 106 elements per second. To achieve such fast printing rate, we implemented a spatial multiplexing of either a single Gaussian or cylindrical vector beams into linear array of identical laser spots. Being compared to ordinary microholes, the coaxial openings arranged at the same periodicity demonstrate enhanced transmission in the mid-IR spectral range resulted from coupling between localized electromagnetic mode supported by coaxial unit cell and the lattice-type surface plasmon resonance. At optimized geometry of the coaxial openings and their arrangement we demonstrated resonant transmission as high as 92% at wavelengths ranging from 7.5 to 9 μm. This makes the coaxial microhole arrays with tailored spectral properties produced with ultrafast and inexpensive direct laser printing promising for sensing applications based on surface enhanced infrared absorption.
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Gizdavec, Nikola, Mateo Gašparović, Slobodan Miko, Borna Lužar-Oberiter, Nikolina Ilijanić, and Zoran Peh. "Discrimination of Rock Units in Karst Terrains Using Sentinel-2A Imagery." Remote Sensing 14, no. 20 (2022): 5169. http://dx.doi.org/10.3390/rs14205169.
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We explored the potential incorporation of Sentinel-2A imagery for rock unit determination in the Croatian karst region dominated by carbonate rocks. The various lithological units are potential sources of both stone aggregates and dimension stone, and their spatial distribution is of high importance for mineral resource management. The presented approach included the preprocessing and processing of existing analog data (geological maps), Sentinel-2A satellite images and the United States Geological Survey spectral indices, all in combination with ground truth data. Geological mapping and digital processing of legacy maps using the K-means and random forest algorithm reduced the spatial error of the geometry of geological boundaries from 100 m and 300 m to below 100 m. The possibility of discriminating individual lithological units based on spectral analysis and discriminant function analysis was also examined, providing a tool for evaluating the geological potential for mineral resources. Despite the challenges posed by the lithological homogeneity of karst terrain, the results of this study show that the use of spectral signature data derived from Sentinel-2A satellite images can be successfully implemented in such terrains for the enhancement of existing geological maps and mineral resources exploration.
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Cayre, F., P. Rondao-Alface, F. Schmitt, Benoı̂t Macq, and H. Maı̂tre. "Application of spectral decomposition to compression and watermarking of 3D triangle mesh geometry." Signal Processing: Image Communication 18, no. 4 (2003): 309–19. http://dx.doi.org/10.1016/s0923-5965(02)00147-9.
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Haider, Usman A., Muhammad Noman, Aamir Rashid, Hatem Rmili, Hidayat Ullah, and Farooq A. Tahir. "A Semi-Octagonal 40-Bit High Capacity Chipless RFID Tag for Future Product Identification." Electronics 12, no. 2 (2023): 349. http://dx.doi.org/10.3390/electronics12020349.
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This paper presents a unique geometry of a chipless radio frequency identification (RFID) tag for encoding a large number of bits in a very small form factor. The tag geometry consists of semi-octagonal copper strips, sequentially laid on a single side of an ultra-thin substrate. A unique and robust encoding mechanism for the tag identification (ID) is proposed. The operating frequency spectrum of the tag ranges from 3.1 to 10.5 GHz. The tag is compact, having an overall size of 14.5 × 28 mm2. The proposed tag exhibits very high code density of 9.85 bits/cm2 and spectral efficiency of 5.4 bits/GHz. The unique geometric configuration of the proposed tag allows it to encode up to 40 bits of data as an RCS signature. This chipless RFID tag seems to be a potential candidate for a wide range of modern RFID applications.
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KLEMENT, STEPHAN, KARL W. KRATKY, and JOHANN NITTMANN. "PRACTICAL TIME-SERIES ANALYSIS WITH MULTIFRACTAL METHODS." Fractals 01, no. 03 (1993): 735–43. http://dx.doi.org/10.1142/s0218348x93000770.
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Time-series data of various origins are studied by analyzing their corresponding multifractal f(α)-spectral which are obtained by use of the so-called canonical method. The classes of data samples under investigation include: (a) airborne particle count data taken from an industrial cleanroom environment; (b) data generated by use of a (pseudo-)random number generator; and (c) data resulting from the iteration of the logistic map for the value r=4.0 of the control parameter, thus exhibiting chaotic behavior. From the resulting multifractal spectra, typical features of the f(α)-curve can be identified in relation to the corresponding class of original data. These findings can be of interest for various purposes. One application under consideration is the processing of microcontamination particle data recorded in high-quality cleanrooms. These are of great importance to the increasing miniaturization of semiconductor devices. In processing microcontamination particle data, the multifractal analysis can help to extract significant information from an enormous number of data to compress these data into a reasonable quantity. Another interesting aspect can be found in using the multifractal spectrum as a possible instrument for estimating the quality and performance of a random number generator.
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Radhadevi, P. V., S. S. Solanki, A. Akilan, M. V. Jyothi, and V. Nagasubramanian. "PERFORMANCE ASSESSMENT AND GEOMETRIC CALIBRATION OF RESOURCESAT-2." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B1 (June 3, 2016): 237–44. http://dx.doi.org/10.5194/isprsarchives-xli-b1-237-2016.
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Resourcesat-2 (RS-2) has successfully completed five years of operations in its orbit. This satellite has multi-resolution and multi-spectral capabilities in a single platform. A continuous and autonomous co-registration, geo-location and radiometric calibration of image data from different sensors with widely varying view angles and resolution was one of the challenges of RS-2 data processing. On-orbit geometric performance of RS-2 sensors has been widely assessed and calibrated during the initial phase operations. Since then, as an ongoing activity, various geometric performance data are being generated periodically. This is performed with sites of dense ground control points (GCPs). These parameters are correlated to the direct geo-location accuracy of the RS-2 sensors and are monitored and validated to maintain the performance. This paper brings out the geometric accuracy assessment, calibration and validation done for about 500 datasets of RS-2. The objectives of this study are to ensure the best absolute and relative location accuracy of different cameras, location performance with payload steering and co-registration of multiple bands. This is done using a viewing geometry model, given ephemeris and attitude data, precise camera geometry and datum transformation. In the model, the forward and reverse transformations between the coordinate systems associated with the focal plane, payload, body, orbit and ground are rigorously and explicitly defined. System level tests using comparisons to ground check points have validated the operational geo-location accuracy performance and the stability of the calibration parameters.
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Radhadevi, P. V., S. S. Solanki, A. Akilan, M. V. Jyothi, and V. Nagasubramanian. "PERFORMANCE ASSESSMENT AND GEOMETRIC CALIBRATION OF RESOURCESAT-2." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B1 (June 3, 2016): 237–44. http://dx.doi.org/10.5194/isprs-archives-xli-b1-237-2016.
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Resourcesat-2 (RS-2) has successfully completed five years of operations in its orbit. This satellite has multi-resolution and multi-spectral capabilities in a single platform. A continuous and autonomous co-registration, geo-location and radiometric calibration of image data from different sensors with widely varying view angles and resolution was one of the challenges of RS-2 data processing. On-orbit geometric performance of RS-2 sensors has been widely assessed and calibrated during the initial phase operations. Since then, as an ongoing activity, various geometric performance data are being generated periodically. This is performed with sites of dense ground control points (GCPs). These parameters are correlated to the direct geo-location accuracy of the RS-2 sensors and are monitored and validated to maintain the performance. This paper brings out the geometric accuracy assessment, calibration and validation done for about 500 datasets of RS-2. The objectives of this study are to ensure the best absolute and relative location accuracy of different cameras, location performance with payload steering and co-registration of multiple bands. This is done using a viewing geometry model, given ephemeris and attitude data, precise camera geometry and datum transformation. In the model, the forward and reverse transformations between the coordinate systems associated with the focal plane, payload, body, orbit and ground are rigorously and explicitly defined. System level tests using comparisons to ground check points have validated the operational geo-location accuracy performance and the stability of the calibration parameters.
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SU, JUNYING, YINGKUI LI, and QINGWU HU. "A NEW SPECTRAL–SPATIAL JOINTED HYPERSPECTRAL IMAGE CLASSIFICATION APPROACH BASED ON FRACTAL DIMENSION ANALYSIS." Fractals 27, no. 05 (2019): 1950079. http://dx.doi.org/10.1142/s0218348x19500798.
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To maximize the advantages of both spectral and spatial information, we introduce a new spectral–spatial jointed hyperspectral image classification approach based on fractal dimension (FD) analysis of spectral response curve (SRC) in spectral domain and extended morphological processing in spatial domain. This approach first calculates the FD image based on the whole SRC of the hyperspectral image and decomposes the SRC into segments to derive the FD images with each SRC segment. These FD images based on the segmented SRC are composited into a multidimensional FD image set in spectral domain. Then, the extended morphological profiles (EMPs) are derived from the image set through morphological open and close operations in spatial domain. Finally, all these EMPs and FD features are combined into one feature vector for a probabilistic support vector machine (SVM) classification. This approach was demonstrated using three hyperspectral images in urban areas of the university campus and downtown area of Pavia, Italy, and the Washington DC Mall area in the USA, respectively. We assessed the potential and performance of this approach by comparing with PCA-based method in hyperspectral image classification. Our results indicate that the classification accuracy of our proposed method is much higher than the accuracies of the classification methods based on the spectral or spatial domain alone, and similar to or slightly higher than the classification accuracy of PCA-based spectral–spatial jointed classification method. The proposed FD approach also provides a new self-similarity measure of land class in spectral domain, a unique property to represent hyperspectral self-similarity of SRC in hyperspectral imagery.
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Bozsik, Éva, Tünde Fórián, Balázs Deák, et al. "Using integrated remote sensing methods in the Nagyerdő Natura 2000 area." Acta Agraria Debreceniensis, no. 55 (February 25, 2014): 19–24. http://dx.doi.org/10.34101/actaagrar/55/1903.
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The more widely use of GIS, remote sensing technology provides appropriate data acquisition and data processing tools to build several national and international biodiversity monitoring system of environmental protection and natur conservation. The ChangeHabitats 2 is a similar international project, which uses airborne hyperspectral and airborne laser scanning (airborne LiDAR) sources beyond traditional data collection methods to build a monitoring system of Natura 2000 habitats. The goal of our research, on one hand, was to separate the most typical species of trees which can be found in the largest coverage in the research plots of Debreceni Nagyerdő Nature Reserve from field and airborne remote sensing data, use image classification that based on spectral and geometry (height) characteristics of the trees. On the other hand our goal was to evaluate the efficient use of the integration of mobilGIS, airborne hyperspectral and airborne LiDAR data collecting methods to complement or substitut of the traditional, field data collecting methods. We used ArcGIS 10.2 and Exelis 5.0 GIS software for data evaluation, in which the mosaicing, the selection of plots and the spectral image processing were carried out.
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Musovic, Jasmin, Vlatko Lipovac, and Adriana Lipovac. "Stochastic Geometry-Based Analysis of Heterogeneous Wireless Network Spectral, Energy and Deployment Efficiency." Electronics 10, no. 7 (2021): 786. http://dx.doi.org/10.3390/electronics10070786.
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For quite a while, it has been evident that homogeneous network architectures, based on cells with a uniform radiation pattern, cannot fulfill the ever increasing demand of mobile users for capacity and service quality while still preserving spectrum and energy. However, only with the introduction of the Fourth Generation mobile communication networks to deal with the surging data traffic of multimedia applications, have smaller cells been widely used to break down service zone areas of macro base stations into multiple tiers, thus improving network performance, reducing traffic congestion, and enabling better management of spectrum and energy consumption in a macro network. In this paper, we present an analytical model for assessing the efficiency of bandwidth and energy usage, as well as of network deployment, taking into account overall network investment and maintenance costs. This paves the way to the improved planning of network coverage, and its capacity and reliability, thus preserving its spectrum and energy, as well as the environment. The analysis considers the downlink of an arbitrary heterogeneous cellular network by using tools of stochastic geometry that adopt the distribution of base stations in the form of a Poisson Point Process. The proposed analytical model is verified by the according software simulations using the ns-3 network simulator. The obtained results closely match the theoretically predicted values and boundaries, clearly indicating that, in all three analyzed aspects: spectral, energy, and deploymental, the efficiency of small-cell networks was higher with respect to traditional large-cell networks and increased even further for heterogeneous (two-tier in our tests) networks.
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Johansson, Sara, Matteo Rossi, Stephen A. Hall, et al. "Combining spectral induced polarization with X-ray tomography to investigate the importance of DNAPL geometry in sand samples." GEOPHYSICS 84, no. 3 (2019): E173—E188. http://dx.doi.org/10.1190/geo2018-0108.1.
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Although many studies have been performed to investigate the spectral induced polarization (SIP) response of nonaqueous phase liquid (NAPL)-contaminated soil samples, there are still many uncertainties in the interpretation of the data. A key issue is that altered pore space geometries due to the presence of a NAPL phase will change the measured IP spectra. However, without any information on the NAPL distribution in the pore space, assumptions are necessary for the SIP data interpretation. Therefore, experimental data of SIP signals directly associated with different NAPL distributions are needed. We used high-resolution X-ray tomography and 3D image processing to quantitatively assess NAPL distributions in samples of fine-grained sand containing different concentrations of tetrachloroethylene and link this to SIP measurements on the same samples. The total concentration of the sample constituents as well as the volumes of the individual NAPL blobs were calculated and used for the interpretation of the associated SIP responses. The X-ray tomography and image analysis showed that the real sample properties (porosity and NAPL distributions) differed from the targeted ones. Both contaminated samples contained less NAPL than expected from the manual sample preparation. The SIP results showed higher real conductivity and lower imaginary conductivity in the contaminated samples compared to a clean sample. This is interpreted as an effect of increased surface conductivity along interconnected NAPL blobs and decreased surface areas in the samples due to NAPL blobs larger than and enclosing grains. We conclude that the combination of SIP, X-ray tomography, and image analysis is a very promising approach to achieve a better understanding of the measured SIP responses of NAPL-contaminated samples.
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Inkinen, Satu I., Mikael A. K. Juntunen, Juuso Ketola, et al. "Virtual monochromatic imaging reduces beam hardening artefacts in cardiac interior photon counting computed tomography: a phantom study with cadaveric specimens." Biomedical Physics & Engineering Express 8, no. 1 (2021): 015029. http://dx.doi.org/10.1088/2057-1976/ac4397.
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Abstract In interior cardiac computed tomography (CT) imaging, the x-ray beam is collimated to a limited field-of-view covering the heart volume, which decreases the radiation exposure to surrounding tissues. Spectral CT enables the creation of virtual monochromatic images (VMIs) through a computational material decomposition process. This study investigates the utility of VMIs for beam hardening (BH) reduction in interior cardiac CT, and further, the suitability of VMIs for coronary artery calcium (CAC) scoring and volume assessment is studied using spectral photon counting detector CT (PCD-CT). Ex vivo coronary artery samples (N = 18) were inserted in an epoxy rod phantom. The rod was scanned in the conventional CT geometry, and subsequently, the rod was positioned in a torso phantom and re-measured in the interior PCD-CT geometry. The total energy (TE) 10–100 keV reconstructions from PCD-CT were used as a reference. The low energy 10–60 keV and high energy 60–100 keV data were used to perform projection domain material decomposition to polymethyl methacrylate and calcium hydroxylapatite basis. The truncated basis-material sinograms were extended using the adaptive detruncation method. VMIs from 30–180 keV range were computed from the detruncated virtual monochromatic sinograms using filtered back projection. Detrending was applied as a post-processing method prior to CAC scoring. The results showed that BH artefacts from the exterior structures can be suppressed with high (≥100 keV) VMIs. With appropriate selection of the monoenergy (46 keV), the underestimation trend of CAC scores and volumes shown in Bland-Altman (BA) plots for TE interior PCD-CT was mitigated, as the BA slope values were −0.02 for the 46 keV VMI compared to −0.21 the conventional TE image. To conclude, spectral PCD-CT imaging using VMIs could be applied to reduce BH artefacts interior CT geometry, and further, optimal selection of VMI may improve the accuracy of CAC scoring assessment in interior PCD-CT.
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Wang, Yang, Xiuqing Hu, Lin Chen, et al. "Comparison of the Lunar Models Using the Hyper-Spectral Imager Observations in Lijiang, China." Remote Sensing 12, no. 11 (2020): 1878. http://dx.doi.org/10.3390/rs12111878.
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A lunar observation campaign was conducted using a hyper-spectral imaging spectrometer in Lijiang, China from December 2015 to February 2016. The lunar hyper-spectral images in the visible to near-infrared region (VNIR) have been obtained in different lunar phases with absolute scale established by the National Institute of Metrology (NIM), China using the lamp–plate calibration system. At the same time, the aerosol optical depth (AOD) is measured regularly by a lidar and a lunar CE318U for atmospheric characterization to provide nightly atmosphere extinction correction of lunar observations. This paper addressed the complicated data processing procedure in detail from raw images of the spectrometer into the spectral lunar irradiance in different lunar phases. The result of measurement shows that the imaging spectrometer can provide lunar irradiance with uncertainties less than 3.30% except for absorption bands. Except for strong atmosphere absorption region, the mean spectral irradiance difference between the measured irradiance and the ROLO (Robotic Lunar Observatory) model is 8.6 ± 2% over the course of the lunar observation mission. The ROLO model performs more reliable to clarify absolute and relative accuracy of lunar irradiance than that of the MT2009 model in different Sun–Moon–Earth geometry. The spectral ratio analysis of lunar irradiance shows that band-to-band variability in the ROLO model is consistent within 2%, and the consistency of the models in the lunar phase and spectrum is well analyzed and evaluated from phase dependence and phase reddening analysis respectively.
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Bimanjaya, Alfian, Hepi Hapsari Handayani, and Reza Fuad Rachmadi. "Extraction of Road Network in Urban Area from Orthophoto Using Deep Learning and Douglas-Peucker Post-Processing Algorithm." IOP Conference Series: Earth and Environmental Science 1127, no. 1 (2023): 012047. http://dx.doi.org/10.1088/1755-1315/1127/1/012047.
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Abstract A Large-scale base map is needed by metropolitan cities such as Surabaya City for urban planning and smart city development. The most needed information from a large-scale base map is road geospatial information. Road network extraction is a challenging task for many reasons, including the heterogeneous attribute of the geometry and spectral, the complexity of objects that are difficult to model, and poor sensor data. Visual interpretation by operators is still a commonly used approach for extracting information from orthophoto. Interpretation accuracy depends on the skill and experience of the operator. So, there can be inconsistencies in the data generated by different operators. In recent years, the automatic extraction of road from orthophoto or VHR image has become an important and challenging research issue. Many recent studies have explored deep learning to improve the quality of building and road extraction. In this study, we applied a Mask Region-based Convolutional Neural Network (Mask R-CNN) model for the road network extraction using orthophoto in urban area in Surabaya City. The quality of the extracted geometry needs to be improved. Several post-processing strategies, including polygon regularization using Douglas-Peucker algorithm and polygon smoothing are designed to achieve optimal extraction results. The method produces a good performance for road extraction, the precision is 90.28%; recall 85.85%; F1-score 88.01%; and IoU 78.59%; and the overall accuracy is 95.25% and the kappa value is 90.5%.
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DAS, ATIN, and PRITHA DAS. "FRACTAL ANALYSIS OF DIFFERENT EASTERN AND WESTERN MUSICAL INSTRUMENTS." Fractals 14, no. 03 (2006): 165–70. http://dx.doi.org/10.1142/s0218348x06003192.
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In this paper, we attempt musical analysis by measuring fractal dimension (D) of musical pieces played by several musical instruments. We collected solo performances of popular instruments of Western and Eastern origin as samples. We attempted usual spectral analysis of the selected clips to observe peaks of fundamental and harmonics in frequency regime. After appropriate processing, we converted them into time series data sets and computed their fractal dimension. Based on our results, we conclude that instrumental musical sounds may have higher Ds than those computed from vocal performances of different types of Indian songs.
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Olsansky, V., C. Granja, C. Oancea, et al. "Spectral-sensitive proton radiography of thin samples with the pixel detector Timepix3." Journal of Instrumentation 17, no. 04 (2022): C04016. http://dx.doi.org/10.1088/1748-0221/17/04/c04016.
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Abstract We evaluate a high-resolution contrast-enhanced method for energy-sensitive radiography of thin samples with low-energy protons at the light-ion Tandetron accelerator of the NPI-CAS in Rez near Prague. We make use of the high-sensitivity of the hybrid semiconductor pixel detectors Timepix enabled by integrated per-pixel signal processing electronics. For this work we use the Timepix3 ASIC chip equipped with a 500 µm Si sensor operated with the fast data rate AdvaPix readout electronics interface. Measurements are performed in air with a 2.9 MeV proton microbeam on thin samples (<100 µm thick). As referential and testing sample we use a set of aluminum foils stacked into a closely packed assembly of varying layers of well-defined thickness. This and other samples were imaged and placed in front of the detector in transmission geometry. Radiographies were collected with focused beam (few mm size) and a microbeam (few µm size). The imaging principle is based on high-resolution spectrometry of single transmitted particles. Contrast is obtained by registration of small differences in the deposited energy of the proton after passing through the sample. This can be measured in wide-range by detailed spectral-tracking analysis of the pixelated clusters in the pixel detector. We examine and evaluate various cluster-track parameters sensitive for imaging contrast such as deposited energy, cluster area (number of pixels) and cluster height (maximum energy value of the pixels in the cluster). The position of interaction in the detector is registered in sub-pixel resolution down to few µm scale for the particles and geometry used. Radiographies are reconstructed based on these individual parameters imaged in image bins of adjustable size (few µm up to few tens of µm). The technique developed with different cluster parameters is presented together with evaluation of image contrast sensitivity on various types of samples and beam energies.
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Kornus, W., A. Magariños, M. Pla, E. Soler, and F. Perez. "PHOTOGRAMMETRIC PROCESSING USING ZY-3 SATELLITE IMAGERY." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-3/W2 (March 10, 2015): 109–13. http://dx.doi.org/10.5194/isprsarchives-xl-3-w2-109-2015.
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This paper evaluates the stereoscopic capacities of the Chinese sensor ZiYuan-3 (ZY-3) for the generation of photogrammetric products. The satellite was launched on January 9, 2012 and carries three high-resolution panchromatic cameras viewing in forward (22º), nadir (0º) and backward direction (-22º) and an infrared multi-spectral scanner (IRMSS), which is slightly looking forward (6º). The ground sampling distance (GSD) is 2.1m for the nadir image, 3.5m for the two oblique stereo images and 5.8m for the multispectral image. The evaluated ZY-3 imagery consists of a full set of threefold-stereo and a multi-spectral image covering an area of ca. 50km x 50km north-west of Barcelona, Spain. The complete photogrammetric processing chain was executed including image orientation, the generation of a digital surface model (DSM), radiometric image correction, pansharpening, orthoimage generation and digital stereo plotting. <br><br> All 4 images are oriented by estimating affine transformation parameters between observed and nominal RPC (rational polynomial coefficients) image positions of 17 ground control points (GCP) and a subsequent calculation of refined RPC. From 10 independent check points RMS errors of 2.2m, 2.0m and 2.7m in X, Y and H are obtained. Subsequently, a DSM of 5m grid spacing is generated fully automatically. A comparison with the Lidar data results in an overall DSM accuracy of approximately 3m. In moderate and flat terrain higher accuracies in the order of 2.5m and better are achieved. In a next step orthoimages from the high resolution nadir image and the multispectral image are generated using the refined RPC geometry and the DSM. After radiometric corrections a fused high resolution colour orthoimage with 2.1m pixel size is created using an adaptive HSL method. The pansharpen process is performed after the individual geocorrection due to the different viewing angles between the two images. In a detailed analysis of the colour orthoimage artifacts are detected covering an area of 4691ha, corresponding to less than 2% of the imaged area. Most of the artifacts are caused by clouds (4614ha). A minor part (77ha) is affected by colour patch, stripping or blooming effects. <br><br> For the final qualitative analysis on the usability of the ZY-3 imagery for stereo plotting purposes stereo combinations of the nadir and an oblique image are discarded, mainly due to the different pixel size, which produces difficulties in the stereoscopic vision and poor accuracy in positioning and measuring. With the two oblique images a level of detail equivalent to 1:25.000 scale is achieved for transport network, hydrography, vegetation and elements to model the terrain as break lines. For settlement, including buildings and other constructions a lower level of detail is achieved equivalent to 1:50.000 scale.
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Tu, Yu-Hsuan, Stuart Phinn, Kasper Johansen, and Andrew Robson. "Assessing Radiometric Correction Approaches for Multi-Spectral UAS Imagery for Horticultural Applications." Remote Sensing 10, no. 11 (2018): 1684. http://dx.doi.org/10.3390/rs10111684.
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Multi-spectral imagery captured from unmanned aerial systems (UAS) is becoming increasingly popular for the improved monitoring and managing of various horticultural crops. However, for UAS-based data to be used as an industry standard for assessing tree structure and condition as well as production parameters, it is imperative that the appropriate data collection and pre-processing protocols are established to enable multi-temporal comparison. There are several UAS-based radiometric correction methods commonly used for precision agricultural purposes. However, their relative accuracies have not been assessed for data acquired in complex horticultural environments. This study assessed the variations in estimated surface reflectance values of different radiometric corrections applied to multi-spectral UAS imagery acquired in both avocado and banana orchards. We found that inaccurate calibration panel measurements, inaccurate signal-to-reflectance conversion, and high variation in geometry between illumination, surface, and sensor viewing produced significant radiometric variations in at-surface reflectance estimates. Potential solutions to address these limitations included appropriate panel deployment, site-specific sensor calibration, and appropriate bidirectional reflectance distribution function (BRDF) correction. Future UAS-based horticultural crop monitoring can benefit from the proposed solutions to radiometric corrections to ensure they are using comparable image-based maps of multi-temporal biophysical properties.
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Norda, M. E., A. Prapiga, P. Paraskevopoulos, and G. A. Tselentis. "A STUDY OF MICROTREMOR HVSR IN THE RIO-ANTIRIO AREA, (GREECE)." Bulletin of the Geological Society of Greece 50, no. 3 (2017): 1194. http://dx.doi.org/10.12681/bgsg.11825.
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Horizontal to Vertical Spectral Ratio (HVSR) method has been applied on ambient noise records at the Rio- Antirio area (central Greece). The dataset used was recorded during 7 days by 12 temporary seismic stations deployed in the area. The stations were laid out along a profile and their interval was approximately 500m. The main part of the processing was done using Geopsy software. The aim of this study was to estimate the fundamental frequency at the station sites and its variation with time and azimuth. The processing results showed that for most stations along the profile, the peaks of the HVSR curve are not strong enough and often there are, more than one, peaks, which seem to be persistent during the whole recording time. When taking the azimuth into account, some of the stations show dominant and persistent directions were the HVSR ratio is stronger, while it has been observed that this direction could vary for different frequency peaks of the same stations. Finally, the top sediment layer’s geometry and thickness were estimated using Vs velocity results from nearby crosshole measurements.
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Krauß, T. "Exploiting Satellite Focal Plane Geometry for Automatic Extraction of Traffic Flow from Single Optical Satellite Imagery." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-1 (November 7, 2014): 179–87. http://dx.doi.org/10.5194/isprsarchives-xl-1-179-2014.
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The focal plane assembly of most pushbroom scanner satellites is built up in a way that different multispectral or multispectral and panchromatic bands are not all acquired exactly at the same time. This effect is due to offsets of some millimeters of the CCD-lines in the focal plane. Exploiting this special configuration allows the detection of objects moving during this small time span. In this paper we present a method for automatic detection and extraction of moving objects – mainly traffic – from single very high resolution optical satellite imagery of different sensors. The sensors investigated are WorldView-2, RapidEye, Pl&eacute;iades and also the new SkyBox satellites. <br><br> Different sensors require different approaches for detecting moving objects. Since the objects are mapped on different positions only in different spectral bands also the change of spectral properties have to be taken into account. In case the main distance in the focal plane is between the multispectral and the panchromatic CCD-line like for Pl&eacute;iades an approach for weighted integration to receive mostly identical images is investigated. Other approaches for RapidEye and WorldView-2 are also shown. From these intermediate bands difference images are calculated and a method for detecting the moving objects from these difference images is proposed. <br><br> Based on these presented methods images from different sensors are processed and the results are assessed for detection quality – how many moving objects can be detected, how many are missed – and accuracy – how accurate is the derived speed and size of the objects. Finally the results are discussed and an outlook for possible improvements towards operational processing is presented.
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Rout, Nibedita, George Baciu, Priyabrata Pattanaik, K. Nakkeeran, and Asimananda Khandual. "Color and Texture Analysis of Textiles Using Image Acquisition and Spectral Analysis in Calibrated Sphere Imaging System-I." Electronics 11, no. 23 (2022): 3887. http://dx.doi.org/10.3390/electronics11233887.
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Numerous imaging applications and analyses demand human perception, and color space transformation of device-dependent tri-band color interpretation (RGB) to device-independent CIE color space standards needs human intervention. The imaging acquisition environment, theoretical conversion errors, viewing geometry, well-defined illumination uniformity, and calibration protocols limit their precision and applicability. It is unfortunate that in most image processing applications, the spectral data are either unavailable or immeasurable. This study is based on developing a novel integrating sphere imaging system and experimentation with textiles’ controlled variation of texture and color. It proposes a simple calibration technique and describes how unique digital color signatures can be derived from calibrated RGB derivatives to extract the best features for color and texture. Additionally, an alter-ego of reflectance function, missing in the imaging domain, is suggested that could be helpful for visualization, identification, and application for qualitative and quantitative color-texture analysis. Our further investigation revealed promising colorimetric results while validating color characterization and different color combinations over three textures.
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He, Yingli, Dongqin Zhao, Zhenqi Fan, An Lu, Xinjiang Xia, and Dongming Wang. "Coverage and Spectral Efficiency of Network Assisted Full Duplex in a Millimeter Wave System." Electronics 11, no. 1 (2021): 5. http://dx.doi.org/10.3390/electronics11010005.
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To cope with the growing trend of asymmetric data traffic, we introduce a novel network assisted full duplex (NAFD) for a millimeter wave system. NAFD can dynamically allocate the number of remote radio heads in the uplink mode or in the downlink mode, which can facilitate simultaneous uplink and downlink communications. In this manuscript, we use stochastic geometry to analyze the distribution of the signal-to-interference-plus-noise ratio and the data rate in a NAFD system. The numerical results verify the analysis and show that the NAFD outperforms the dynamic time division duplex system and the traditional flexible duplex system in terms of spectral efficiency.
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Bai, Ling, Yinguo Li, and Ming Cen. "Dynamic Intervisibility Analysis of 3D Point Clouds." ISPRS International Journal of Geo-Information 10, no. 11 (2021): 782. http://dx.doi.org/10.3390/ijgi10110782.
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With the popularity of ground and airborne three-dimensional laser scanning hardware and the development of advanced technologies for computer vision in geometrical measurement, intelligent processing of point clouds has become a hot issue in artificial intelligence. The intervisibility analysis in 3D space can use viewpoint, view distance, and elevation values and consider terrain occlusion to derive the intervisibility between two points. In this study, we first use the 3D point cloud of reflected signals from the intelligent autonomous driving vehicle’s 3D scanner to estimate the field-of-view of multi-dimensional data alignment. Then, the forced metrics of mechanical Riemann geometry are used to construct the Manifold Auxiliary Surface (MAS). With the help of the spectral analysis of the finite element topology structure constructed by the MAS, an innovative dynamic intervisibility calculation is finally realized under the geometric calculation conditions of the Mix-Planes Calculation Structure (MPCS). Different from advanced methods of global and interpolation pathway-based point clouds computing, we have removed the 99.54% high-noise background and reduced the computational complexity by 98.65%. Our computation time can reach an average processing time of 0.1044 s for one frame with a 25 fps acquisition rate of the original vision sensor. The remarkable experimental results and significant evaluations from multiple runs demonstrate that the proposed dynamic intervisibility analysis has high accuracy, strong robustness, and high efficiency. This technology can assist in terrain analysis, military guidance, and dynamic driving path planning, Simultaneous Localization And Mapping (SLAM), communication base station siting, etc., is of great significance in both theoretical technology and market applications.
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Miclea, Andreia Valentina, Romulus Mircea Terebes, Serban Meza, and Mihaela Cislariu. "On Spectral-Spatial Classification of Hyperspectral Images Using Image Denoising and Enhancement Techniques, Wavelet Transforms and Controlled Data Set Partitioning." Remote Sensing 14, no. 6 (2022): 1475. http://dx.doi.org/10.3390/rs14061475.
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Obtaining relevant classification results for hyperspectral images depends on the quality of the data and the proposed selection of the samples and descriptors for the training and testing phases. We propose a hyperspectral image classification machine learning framework based on image processing techniques for denoising and enhancement and a parallel approach for the feature extraction step. This parallel approach is designed to extract the features by employing the wavelet transform in the spectral domain, and by using Local Binary Patterns to capture the texture-like information linked to the geometry of the scene in the spatial domain. The spectral and spatial features are concatenated for a Support Vector Machine-based supervised classifier. For the experimental validation, we propose a controlled sampling approach that ensures the independence of the selected samples for the training data set, respectively the testing data set, offering unbiased performance results. We argue that a random selection applied on the hyperspectral dataset to separate the samples for the learning and testing phases can cause overlapping between the two datasets, leading to biased classification results. The proposed approach, with the controlled sampling strategy, tested on three public datasets, Indian Pines, Salinas and Pavia University, provides good performance results.
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Yang, Ye, Yongli Hu, and Fei Wu. "Sparse and Low-Rank Subspace Data Clustering with Manifold Regularization Learned by Local Linear Embedding." Applied Sciences 8, no. 11 (2018): 2175. http://dx.doi.org/10.3390/app8112175.
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Data clustering is an important research topic in data mining and signal processing communications. In all the data clustering methods, the subspace spectral clustering methods based on self expression model, e.g., the Sparse Subspace Clustering (SSC) and the Low Rank Representation (LRR) methods, have attracted a lot of attention and shown good performance. The key step of SSC and LRR is to construct a proper affinity or similarity matrix of data for spectral clustering. Recently, Laplacian graph constraint was introduced into the basic SSC and LRR and obtained considerable improvement. However, the current graph construction methods do not well exploit and reveal the non-linear properties of the clustering data, which is common for high dimensional data. In this paper, we introduce the classic manifold learning method, the Local Linear Embedding (LLE), to learn the non-linear structure underlying the data and use the learned local geometry of manifold as a regularization for SSC and LRR, which results the proposed LLE-SSC and LLE-LRR clustering methods. Additionally, to solve the complex optimization problem involved in the proposed models, an efficient algorithm is also proposed. We test the proposed data clustering methods on several types of public databases. The experimental results show that our methods outperform typical subspace clustering methods with Laplacian graph constraint.
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Jurado, J. M., L. Ortega, J. J. Cubillas, and F. R. Feito. "Multispectral Mapping on 3D Models and Multi-Temporal Monitoring for Individual Characterization of Olive Trees." Remote Sensing 12, no. 7 (2020): 1106. http://dx.doi.org/10.3390/rs12071106.
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3D plant structure observation and characterization to get a comprehensive knowledge about the plant status still poses a challenge in Precision Agriculture (PA). The complex branching and self-hidden geometry in the plant canopy are some of the existing problems for the 3D reconstruction of vegetation. In this paper, we propose a novel application for the fusion of multispectral images and high-resolution point clouds of an olive orchard. Our methodology is based on a multi-temporal approach to study the evolution of olive trees. This process is fully automated and no human intervention is required to characterize the point cloud with the reflectance captured by multiple multispectral images. The main objective of this work is twofold: (1) the multispectral image mapping on a high-resolution point cloud and (2) the multi-temporal analysis of morphological and spectral traits in two flight campaigns. Initially, the study area is modeled by taking multiple overlapping RGB images with a high-resolution camera from an unmanned aerial vehicle (UAV). In addition, a UAV-based multispectral sensor is used to capture the reflectance for some narrow-bands (green, near-infrared, red, and red-edge). Then, the RGB point cloud with a high detailed geometry of olive trees is enriched by mapping the reflectance maps, which are generated for every multispectral image. Therefore, each 3D point is related to its corresponding pixel of the multispectral image, in which it is visible. As a result, the 3D models of olive trees are characterized by the observed reflectance in the plant canopy. These reflectance values are also combined to calculate several vegetation indices (NDVI, RVI, GRVI, and NDRE). According to the spectral and spatial relationships in the olive plantation, segmentation of individual olive trees is performed. On the one hand, plant morphology is studied by a voxel-based decomposition of its 3D structure to estimate the height and volume. On the other hand, the plant health is studied by the detection of meaningful spectral traits of olive trees. Moreover, the proposed methodology also allows the processing of multi-temporal data to study the variability of the studied features. Consequently, some relevant changes are detected and the development of each olive tree is analyzed by a visual-based and statistical approach. The interactive visualization and analysis of the enriched 3D plant structure with different spectral layers is an innovative method to inspect the plant health and ensure adequate plantation sustainability.
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Artyukov, Igor A., Nikolay L. Popov, and Alexander V. Vinogradov. "Lensless Reflection Imaging of Obliquely Illuminated Objects I: Choosing a Domain for Phase Retrieval and Ptychography." Symmetry 13, no. 8 (2021): 1439. http://dx.doi.org/10.3390/sym13081439.
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Ptychography is a lensless imaging technology that is validated from hard X-rays to terahertz spectral range. It is most attractive for extreme ultraviolet (EUV) and X-rays as optical elements are expensive and often not available. Typically, the set up involves coherently illuminated object that directs the scattered radiation normally to detector which is parallel to the object plane. Computer processing of diffraction patterns obtained when scanning the object gives the image, more precisely, the distribution of intensity and phase on its surface. However, this scheme is inefficient for EUV and X-rays due to poor reflectivity and low penetration in all materials. Reflection mode ptychography solves the problem if illumination angles do not exceed the critical angle of object material. Changing the geometry of experiment changes physical and mathematical model of image formation. Including: diffraction integral describing beam propagation from object to detector, inverse problem, optimization of object illumination angle, position and orientation of detector, choosing size and grid of coordinate and frequency computer domains. This paper considers the wavefield scattered to detector by obliquely illuminated object and determines a domain for processing of obtained scans. Solution of inverse problem with phase retrieval and resulting numerical images will be presented in the next paper.
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Trokhimovskiy, A., V. Perevalov, O. Korablev та ін. "First observation of the magnetic dipole CO2 absorption band at 3.3 μm in the atmosphere of Mars by the ExoMars Trace Gas Orbiter ACS instrument". Astronomy & Astrophysics 639 (липень 2020): A142. http://dx.doi.org/10.1051/0004-6361/202038134.
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The atmosphere of Mars is dominated by CO2, making it a natural laboratory for studying CO2 spectroscopy. The Atmospheric Chemistry Suite (ACS) on board the ExoMars Trace Gas Orbiter uses solar occultation geometry to search for minor atmospheric species. During the first year of ACS observations, the attention was focused on the spectral range covering the methane ν3 absorption band, 2900–3300 cm−1, which has previously been observed on Mars. No methane was detected by ACS; instead, an improvement of the data processing has led to the identification of 30 weak absorption lines that were missing from spectroscopic databases. Periodic series of absorptions up to ~1.6% deep are observed systematically around the position of the methane Q-branch when the line of sight penetrates below 20 km (creating an optical path length of 300–400 km, with an effective pressure of a few millibar). The observed frequencies of the discovered lines match theoretically computed positions of the P-, Q-, and R-branches of the magnetic dipole and electric quadrupole 01111-00001 (ν2 + ν3) absorption bands of the main CO2 isotopologue; neither band has been measured or computed before. The relative depths of the observed spectral features support the magnetic dipole origin of the band. The contribution of the electric quadrupole absorption is several times smaller. Here we report the first observational evidence of a magnetic dipole CO2 absorption.
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Drexler, Petr, Dušan Nešpor, Radim Kadlec, Tomáš Kříž, and Alois Nebojsa. "Simulation and Characterization of Nanostructured Electromagnetic Scatterers for Information Encoding." Electronics 11, no. 20 (2022): 3283. http://dx.doi.org/10.3390/electronics11203283.
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Nanostructured scattering arrays for the optical spectral domain can be used as passive tags for information encoding, similarly to the manner in which RFID technology does. Setting up their specific spectral response depends on their geometry and the properties of the building materials. The primary design can be provided by using an analytical calculation procedure that is more straightforward and simpler than a numerical simulation. However, the question arises as to the validity of the results. Both approaches are examined in this article. Complementary scatterer arrays were designed using simplified analytical calculation and by means of numerical modeling. The experimental samples were fabricated by the focused ion beam milling of a gold film on a glass substrate and characterized by a spectroscopic system. The results of the analytical calculations, the numerical simulations, and the experimental measurements were compared. On the basis of the comparison, it was observed that for quick array design, both approaches can be used with satisfactory accuracy. Moreover, the simple numerical model also proved the possibility of the identification of the basic dipole mode splitting. Focused ion beam milling was shown to be suitable for the rapid production of complementary scatterer arrays.
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Kolbudaev, Pavel, Dmitry Plotnikov, Evgeny Loupian, Andrey Proshin, and Alexey Matveev. "The methods and automatic technology aimed at imagery georeferencing, cloud screening, atmospheric and radiometric correction of KMSS-M satellite data." E3S Web of Conferences 333 (2021): 01006. http://dx.doi.org/10.1051/e3sconf/202133301006.
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In this study we present methods and automatic technology developed for routine processing of satellite imagery acquired by cameras MSU-201 and MSU-202 (KMSS-M) onboard Meteor-M №2. The developed methods were aimed at imagery georeferencing issues fixing, clouds and shadows detection as well as atmospheric and radiometric correction. Basing on these methods we built an automatic technology and complete KMSS-M data processing chain which provided analysis ready dataset for Russian grain belt and adjacent areas of neighboring countries for the year 2020. Method for imagery georeferencing was based on Pearson’s correlation localized maximization when compared to the georefenced and cloudfree coarse-resolution reference image produced in IKI RAS through MOD09 product time series processing. Method for clouds and shadows detection was based both on the spatial analysis of outputs from geocorrection step and auxiliary image, characterizing georeferenced KMSS-M image values relative accordance with the IKI reference image. The atmospheric correction was based on localized histogram matching of KMSS-M and IKI reference date-corresponding imagery, and thereby concurrently performed radiometric correction of KMSS-M data, compensating effects of varying viewing and illumination geometry which explicitly manifest across 960-km-wide swath area. The developed methods are noticeably minimalistic, requiring only one target spectral band to perform properly. Due to high flexibility and robustness, they also may be applied to raw satellite imagery acquired from various Earth observation systems, including Russian systems of high and moderate spatial resolution. The technology is currently being deployed in an operative mode for several test sites of Russia since the year 2021 onwards.
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Fiandaca, Gianluca, Per-Ivar Olsson, Pradip Kumar Maurya, et al. "Heterodox transients in time-domain-induced polarization." GEOPHYSICS 87, no. 1 (2021): E35—E47. http://dx.doi.org/10.1190/geo2020-0808.1.
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Negative-induced polarization (IP) time-domain transients, sign-changing or nonmonotonically decaying transients, are currently often considered as measurement errors and are removed in data processing. These transients, here called heterodox in the sense of other than generally accepted signals, might originate from measurement errors, inductive effects, or poor signal processing, but synthetic modeling and field measurements indicate that these transients are physically possible. A simple theoretical explanation of the basic mechanism for their origin can be found through the superposition of contributions from regions with different sensitivities, and such heterodox transients can be identified through the processing of full-waveform IP data. A mathematical classification of orthodox and heterodox IP transients into six different types is evaluated based on the temporal development of the sign of their amplitude and derivative. The basic mechanism for IP transients with heterodox shapes is further investigated by considering the subsurface Cole-Cole parameter sensitivities and time-varying IP potential for 2D synthetic models. The time-domain forward response and sensitivities are computed through a time transformation that accounts for the current waveform. This approach allows for quantitative unbiased estimates of the time-domain transients and sensitivities, different from the estimates obtained when using multiple direct-current forward computations, as is often done in the inversion of time-domain IP data. Time-domain IP transients may differ from the traditionally expected decaying-like transients when the electrode geometry has IP potential sensitivities with different signs for areas with different IP parameters. Hence, previously disregarded IP transients containing valuable information of the subsurface can be kept for inversion and contribute to the final parameter distribution. An increased understanding of theoretically possible IP transients makes way for more accurate processing of data in the future, reducing the time and resources needed for spectral inversion of time-domain data.
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Bacour, Cédric, François-Marie Bréon, Louis Gonzalez, Ivan Price, Jan-Peter Muller, and Anne Straume. "Simulating Multi-Directional Narrowband Reflectance of the Earth’s Surface Using ADAM (A Surface Reflectance Database for ESA’s Earth Observation Missions)." Remote Sensing 12, no. 10 (2020): 1679. http://dx.doi.org/10.3390/rs12101679.
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The ADAM (A Surface Reflectance Database for ESA’s Earth Observation Missions) product (a climatological database coupled to its companion calculation toolkit) enables users to simulate realistic hyperspectral and directional global Earth surface reflectances (i.e., top-of-canopy/bottom-of-atmosphere) over the 240–4000 nm spectral range (at 1-nm resolution) and in any illumination/observation geometry, at 0.1° × 0.1° spatial resolution for a typical year. ADAM aims to support the preparation of optical Earth observation missions as well as the design of operational processing chains for the retrieval of atmospheric parameters by characterizing the expected surface reflectance, accounting for its anisotropy. Firstly, we describe (1) the methods used in the development of the gridded monthly ADAM climatologies (over land surfaces: monthly means of normalized reflectances derived from MODIS observations in seven spectral bands for the year 2005; over oceans: monthly means over the 1999–2009 period of chlorophyll content from SeaWiFS and of wind speed from SeaWinds), and (2) the underlying modeling approaches of ADAM toolkit to simulate the spectro-directional variations of the reflectance depending on the assigned surface type. Secondly, we evaluate ADAM simulation performances over land surfaces. A comparison against POLDER multi-spectral/multi-directional measurements for year 2008 shows reliable simulation results with root mean square differences below 0.027 and R2 values above 0.9 for most of the 14 land cover IGBP classes investigated, with no significant bias identified. Only for the “Snow and ice” class is the performance lower pointing to a limitation of climatological data to represent actual snow properties. An evaluation of the modeled reflectance in the specific backscatter direction against CALIPSO data reveals that ADAM tends to overestimate (underestimate) the so-called “hot-spot” by a factor of about 1.5 (1.5 to 2) for barren (vegetated) surfaces.
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Shen, Xuejian, Mark Vogelsberger, Dylan Nelson, et al. "High-redshift JWST predictions from IllustrisTNG: II. Galaxy line and continuum spectral indices and dust attenuation curves." Monthly Notices of the Royal Astronomical Society 495, no. 4 (2020): 4747–68. http://dx.doi.org/10.1093/mnras/staa1423.
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ABSTRACT We present predictions for high redshift (z = 2−10) galaxy populations based on the IllustrisTNG simulation suite and a full Monte Carlo dust radiative transfer post-processing. Specifically, we discuss the H α and H β + $[\rm O \,{\small III}]$ luminosity functions up to z = 8. The predicted H β + $[\rm O \,{\small III}]$ luminosity functions are consistent with present observations at z ≲ 3 with ${\lesssim} 0.1\, {\rm dex}$ differences in luminosities. However, the predicted H α luminosity function is ${\sim }0.3\, {\rm dex}$ dimmer than the observed one at z ≃ 2. Furthermore, we explore continuum spectral indices, the Balmer break at 4000 Å; (D4000) and the UV continuum slope β. The median D4000 versus specific star formation rate relation predicted at z = 2 is in agreement with the local calibration despite a different distribution pattern of galaxies in this plane. In addition, we reproduce the observed AUV versus β relation and explore its dependence on galaxy stellar mass, providing an explanation for the observed complexity of this relation. We also find a deficiency in heavily attenuated, UV red galaxies in the simulations. Finally, we provide predictions for the dust attenuation curves of galaxies at z = 2−6 and investigate their dependence on galaxy colours and stellar masses. The attenuation curves are steeper in galaxies at higher redshifts, with bluer colours, or with lower stellar masses. We attribute these predicted trends to dust geometry. Overall, our results are consistent with present observations of high-redshift galaxies. Future James Webb Space Telecope observations will further test these predictions.
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Ngcofe, Luncedo, and Nale Mudau. "An investigation of geographic object based image analysis (GEOBIA) for human settlement detection in South Africa." Abstracts of the ICA 1 (July 15, 2019): 1. http://dx.doi.org/10.5194/ica-abs-1-269-2019.
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<p><strong>Abstract.</strong> The changes to the landscape are constantly occurring both naturally and human induced. One of such changes is the human settlement expansion. The ability to map human settlements is vital for variety of studies including urban development planning and management. For this study human settlement detection is essential for topographic map update. The newly identified human settlements also serves as change detection area indicator for further update of other topographic features that are represented on the topographic map (such as roads etc.). The semi-automated human settlement detection has been conducted through geographic object based image analysis (GEOBIA) method using 2012 SPOT 5 imagery in the KwaZulu-Natal Province of South Africa. GEOBIA is relative new development of image processing and analysis of remote sensed imagery. It involves partitioning an imagery into discrete entities or segments from which meaningful image object, based on the spatial and spectral attributes can be generated. Through a multiresolution segmentation model implemented by the eCognition software, image segmentation was attained. This entailed evaluation of different segmentation parameter in order obtain suitable objects of interest. The following step was to determine appropriate variables obtained from image segmentation to classify the image. These include: layer values, geometry, position, texture, hierarchy and thematic attributes. The layer value option entails spectral statistics such as mean value and mean brightness for image reflectance bands together with capability of further applying band ratio combinations. Under the texture and geometry option also several alternatives are applicable (such as length/width under extend and asymmetry under shape properties). Under the level co-occurrence matrix (GLCM) the study explored the contrast textual measurements developed by Haralick et al., (1973). Other assessed variables are mean brightness, density, length/width and band ratios. The last step for GEOBIA was to determine suitable variables for the rule-set based classification. This resulted to 70.7% overall accuracy.</p><p>These results were further compared to the existing South African global human settlement layer (SA_GHSL) for the same study area which also used the same year 2012 SPOT 5 imagery. The SA_GHSL had an overall accuracy of 60%. The GEOBIA presents an opportunity to apply semi-automated method to target areas of new settlement development more efficiently and with consistent repeatable manner. Thus assisting topographic update analyst to be drawn to more areas of new settlement development at an enhanced efficient rate. However the spectral variability of roof tops proved to be the most challenging obstacle towards of both the semi-automated settlement detection methods.</p>
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Yu, Wang, Li, Chang, and Li. "Snow Depth Estimation with GNSS-R Dual Receiver Observation." Remote Sensing 11, no. 17 (2019): 2056. http://dx.doi.org/10.3390/rs11172056.
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Two estimation methods using a dual GNSS (Global Navigation Satellite System) receiver system are proposed. The dual-frequency combination method combines the carrier phase observations of dual-frequency signals, whereas the single-frequency combination method combines the pseudorange and carrier phase observations of a single-frequency signal, both of which are geometry-free strictly combination and free of the effect of ionospheric delay. Theoretical models are established in the offline phase to describe the relationship between the spectral peak frequency of the combined sequence and the antenna height. A field experiment was conducted recently and the data processing results show that the root mean squared error (RMSE) of the dual-frequency combination method is 5.04 cm with GPS signals and 6.26 cm with BDS signals, which are slightly greater than the RMSE of 4.16 cm produced by the single-frequency combination method of L1 band with GPS signals. The results also demonstrate that the proposed two combination methods and the SNR method achieve similar performance. A dual receiver system enables the better use of GNSS signal carrier phase observations for snow depth estimation, achieving increased data utilization.
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Chiang, Chia Chin, Cheung Hwa Hsu, and Chao Hui Ou. "pH Value Detection with CLPFG Sensor." Applied Mechanics and Materials 284-287 (January 2013): 2157–61. http://dx.doi.org/10.4028/www.scientific.net/amm.284-287.2157.
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Detection of pH value plays an important role in many fields; the precise measurement of pH value is very useful in Living systems, Chemistry and Biochemistry. The purpose of this paper is to measure pH value in solution by using Corrugated Long Period Fiber Grating (CLPFG). The CLPFG element is highly sensitive to refractive index changes, and with appropriate design geometry; a variety of target molecules can then be detected. Optical fiber Corrugated Long Period Gratings are designed to act as spectral loss elements that couple with a discrete wavelength out of the optical fiber as a function of the surrounding refractive index. By applying special coating that change refractive index with absorption of target molecules to the CLPFG surface, it became a transducer for chemical measurement. In this paper, it has shown the incorporation of Polyvinyl Alcohol and Polycyclic Acid (PVA-PAA) with Corrugated Long Period Gratings for the development of a fiber optic-based pH sensor with the detection of pH range from 3 to 6. Optical fiber-based pH sensors offer numerous advantages in wastewater monitoring, remote blood diagnostics, bioremediation, as well as chemical and food processing.
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Labson, V. F., A. Becker, H. F. Morrison, and U. Conti. "Geophysical exploration with audiofrequency natural magnetic fields." GEOPHYSICS 50, no. 4 (1985): 656–64. http://dx.doi.org/10.1190/1.1441940.
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Experience with the AFMAG method has demonstrated that an electromagnetic exploration system using the Earth’s natural audiofrequency magnetic fields as an energy source is capable of mapping subsurface electrical structure in the upper kilometer of the Earth’s crust. We resolved the limitations of this method by adapting the tensor analysis and remote reference noise bias removal techniques from the geomagnetic induction and magnetotelluric methods to computation of the tippers. After a thorough spectral study of the natural magnetic fields, we designed lightweight magnetic field sensors capable of measuring the magnetic field throughout the year. We also built a digital acquisition and processing system with the ability to provide audiofrequency tipper results in the field. This new instrumentation was used in a study of the Mariposa, California site previously mapped with AFMAG. This study once again demonstrates the usefulness of natural magnetic field data in mapping an electrically conductive body. Reoccupation of one of the sites in several different seasons proves the high level of repeatability of these data. As well as being repeatable, the tensor data provide additional information on the geometry of the conductive body. Different electrical conductivity features can be distinguished using a broad band of frequencies.