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1
Xiang, Hongyin, Jinsha Yuan, and Sizu Hou. "Hybrid Predictor and Field-Biased Context Pixel Selection Based on PPVO." Mathematical Problems in Engineering 2016 (2016): 1–16. http://dx.doi.org/10.1155/2016/2585983.
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Most pixel-value-ordering (PVO) predictors generated prediction-errors including −1 and 1 in a block-by-block manner. Pixel-based PVO (PPVO) method provided a novel pixel scan strategy in a pixel-by-pixel way. Prediction-error bin 0 is expanded for embedding with the help of equalizing context pixels for prediction. In this paper, a PPVO-based hybrid predictor (HPPVO) is proposed as an extension. HPPVO predicts pixel in both positive and negative orientations. Assisted by expansion bins selection technique, this hybrid predictor presents an optimized prediction-error expansion strategy including bin 0. Furthermore, a novel field-biased context pixel selection is already developed, with which detailed correlations of around pixels are better exploited more than equalizing scheme merely. Experiment results show that the proposed HPPVO improves embedding capacity and enhances marked image fidelity. It also outperforms some other state-of-the-art methods of reversible data hiding, especially for moderate and large payloads.
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Heymes, J., J. Ivory, K. Stefanov, T. Buggey, O. Hetherington, M. Soman, and A. Holland. "Characterisation of a soft X-ray optimised CMOS Image Sensor." Journal of Instrumentation 17, no. 05 (May 1, 2022): P05003. http://dx.doi.org/10.1088/1748-0221/17/05/p05003.
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Abstract A prototype CMOS Image Sensor optimised for soft X-ray applications has been designed by the Centre for Electronic Imaging in partnership with Teledyne-e2v. The device features four different pixel variants (three variants of 40 μm pitch pixels, and one variant of 10 μm pixels) each covering a quarter of the 2 × 2 cm2 image area. The pixel designs feature fully depleted pinned photodiodes using reverse substrate bias and have been optimised for low noise operation, high responsivity and low image lag. The fabricated front-illuminated devices have been tested in a custom-built vacuum test setup at operating temperatures between -30°C and -40°C. The sensors feature less than 5 e- RMS readout noise and energy resolution of 142 eV at Mn-Kα (5.9 keV). The response to soft X-ray with different sensor parameters (e.g. pixel pitch, deep-depletion extension implant depth, and back-bias voltage) is also studied.
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Urban, K., M. Carminati, M. Descher, F. Edzards, D. Fink, C. Fiorini, M. Gugiatti, et al. "Characterization measurements of the TRISTAN multi-pixel silicon drift detector." Journal of Instrumentation 17, no. 09 (September 1, 2022): C09020. http://dx.doi.org/10.1088/1748-0221/17/09/c09020.
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Abstract Sterile neutrinos are a minimal extension of the standard model of particle physics. A laboratory-based approach to search for this particle is via tritium β-decay, where a sterile neutrino would cause a kink-like spectral distortion. The Karlsruhe Tritium Neutrino (KATRIN) experiment extended by a multi-pixel Silicon Drift Detector system has the potential to reach an unprecedented sensitivity to the keV-scale sterile neutrino in a lab-based experiment. The new detector system combines good spectroscopic performance with a high rate capability. In this work, we report about the characterization of charge-sharing between pixels and the commissioning of a 47-pixel prototype detector in a MAC-E filter.
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Subasinghe, Shyamantha. "Urban Growth: From pixel to reality." Abstracts of the ICA 1 (July 15, 2019): 1. http://dx.doi.org/10.5194/ica-abs-1-353-2019.
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<p><strong>Abstract.</strong> Urban growth is a complex process created through the interaction of human and environmental conditions. The spatial configuration and dynamic process of urban growth is an important topic in contemporary geographical studies (Thapa and Murayama, 2010). However, urban growth pattern recognition is a challengeable task and it has become one of the major fields in Cartography. Since classical era of cartography, several methods have been employed in modelling and urban growth pattern recognition. It shows that there is no agreement among cartographer or any other spatial scientists on how to map the diverse patterns of urban growth.</p><p>Typical urban theories such as von Thünen’s (1826) bid-rent theory, Burgess’s (1925) concentric zone model, Christaller’s (1933) central place theory, and Hoyt’s (1939) sector model explain the urban structure in different manner. Most of them do not contribute to visualize the urban growth pattern spatiotemporally. Recently, by addressing this limitations, several sophisticated methods are used in urban growth visualization. Among them, morphological spatial pattern analysis (MSPA) is one of emerging raster data analysis methods which allows us to integrate neighbourhood interaction rules in urban growth pattern recognition and visualization. Angel et al. (2010) developed urban land classification (urban, suburban, rural, fringe open space, exterior open space, and rural open space) based on built and non-built land categories and detected three major types of urban growth (infill, extension, and leapfrog). However, developing urban land classifications using binary land use type and recognising only three types of urban growth pattern may be insufficient due to the existence of a higher complexity of urban growth. In such context, the present study introduce a geovisualization approach to map spatial patterns of urban growth using multiple land categories and develops three sub-levels of urban growth pattern for each major urban growth pattern.</p><p>The entire process of urban growth pattern recognition developed in this study can be summarized into three steps (Figure 1): (1) urban land mapping &ndash; Landsat imageries representing two time points (2001 and 2017) were classified into two land categories (built and non-built) and developed into multiple classes using ancillary data, (2) recognizing three major patterns of urban growth (infill, extension, and leapfrog) &ndash; the raster overlay method based on neighbourhood interaction rules, (3) development of sublevels of urban growth &ndash; major three patterns were further developed and visualized nine urban growth patterns, namely low infill (LI), moderate infill (MI), high infill (HI), low extension (LE), moderate extension (ME), high extension (HE), low leapfrog (LL), moderate leapfrog (ML), and high leapfrog (HL). The developed procedure of this study in urban growth pattern recognition was tested using a case study of Colombo metropolitan area, Sri Lanka.</p>
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Straasø, Tine, Dirk Müter, Henning Osholm Sørensen, and Jens Als-Nielsen. "Objective algorithm to separate signal from noise in a Poisson-distributed pixel data set." Journal of Applied Crystallography 46, no. 3 (April 18, 2013): 663–71. http://dx.doi.org/10.1107/s0021889813006511.
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A statistical method to determine the background level and separate signal from background in a Poisson-distributed background data set is described. The algorithm eliminates the pixel with the highest intensity value in an iterative manner until the sample variance equals the sample mean within the estimated uncertainties. The eliminated pixels then contain signal superimposed on the background, so the integrated signal can be obtained by summation or by a simple extension by profile fitting depending on the user's preferences. Two additional steps remove `outliers' and correct for the underestimated extension of the peak area, respectively. The algorithm can be easily modified to specific needs, and an application on crystal truncation rods is presented, dealing with a sloping background.
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GAO, ZHIYUAN, SUYING YAO, JIANGTAO XU, and CHAO XU. "DYNAMIC RANGE EXTENSION OF CMOS IMAGE SENSORS USING MULTI-INTEGRATION TECHNIQUE WITH COMPACT READOUT." Journal of Circuits, Systems and Computers 22, no. 06 (July 2013): 1350042. http://dx.doi.org/10.1142/s0218126613500424.
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A multi-integration technology with compact readout method to extend CMOS image sensor's dynamic range is presented. Compared with the timing of rolling readout, compact readout extends the available pixel readout time by adjusting the time-domain offset between two adjacent rows and each integration time in one frame. Thus the column readout bus is working continuously rather than intermittently, which makes good use of the whole integration time and the available readout time can be extended. This dynamic range extension technology was implemented on a prototype chip with a 128 × 128 pixel array. The pixel readout time with compact readout method is almost as 3 times long as the one with rolling readout method while 39 dB dynamic range extension is achieved at 120 fps.
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Dingley, David J. "Extension of Orientation Mapping to the Transmission Electron Microscope." Materials Science Forum 495-497 (September 2005): 225–30. http://dx.doi.org/10.4028/www.scientific.net/msf.495-497.225.
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This paper describes progress in improving the spatial resolution of the well-established Orientation Imaging Microscopy technique, OIM, by developing an analogous procedure for the transmission electron microscope. The transmission orientation micrographs are obtained by recording a large series of dark field micrographs taken from the chosen area in the specimen. This area is selected so that it contains all of the grains of interest and is imaged at sufficiently high magnification to yield the spatial resolution required. The changing intensity of each pixel in different dark field micrographs permits the equivalent of a diffraction pattern for that pixel to be constructed. This enables determination of the lattice orientation of small volumes in the sample corresponding to that imaged in each individual pixel. Experimentation has shown that problems arise however, that decrease the fraction of correctly measured points due to ambiguities in determining the index of higher order reflections, especially when the total number of reflections observed is small. The solution has been to both modify the indexing procedure and to sum the diffraction vectors observed within a single grain. The paper concentrates on a detailed analysis of a heavily deformed aluminium sample, chosen because of the fragmentation of the structure.
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Zhao, Ge, Ying Kui Du, and Yan Dong Tang. "A New Extension of the Rank Transform for Stereo Matching." Advanced Engineering Forum 2-3 (December 2011): 182–87. http://dx.doi.org/10.4028/www.scientific.net/aef.2-3.182.
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Stereo matching methods often use rank transform to deal with image distortions and brightness differences prior to matching but a pixel in the rank transformed image may look more similar to its neighbor, which would cause matching ambiguity. We tackle this problem with two proposals. Firstly, instead of using two values 0 and 1,we increase the discriminative power of the rank transform by using a linear, smooth transition zone between 0 and 1 for intensities that are close together. Secondly, we propose a new Bayesian stereo matching model by not only considering the similarity between left and right image pixels but also considering the ambiguity level of them in their own image independently. We test our algorithm on both intensity and color images with brightnesss differences. Corresponding 2D disparity maps and 3D reconstruction results verify the effectiveness of our method.
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Liu, Yifan, Zhenjiang Cai, and Xuesong Suo. "A Multiframes Integration Object Detection Algorithm Based on Time-Domain and Space-Domain." Mathematical Problems in Engineering 2018 (2018): 1–15. http://dx.doi.org/10.1155/2018/4127305.
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In order to overcome the disadvantages of the commonly used object detection algorithm, this paper proposed a multiframes integration object detection algorithm based on time-domain and space-domain (MFITS). At first, the consecutive multiframes were observed in time-domain. Then the horizontal and vertical four-direction extension neighborhood of each target pixel were selected in space-domain. Transverse and longitudinal sections were formed by fusing of the time-domain and space-domain. The mean and standard deviation of the pixels in transverse and longitudinal section were calculated. We also added an improved median filter to generate a new pixel in each target pixel position, eventually to generate a new image. This method is not only to overcome the RPAC method affected by lights, shadows, and noise, but also to reserve the object information to the maximum compared with the interframe difference method and overcome the difficulty in dealing with the high frequency noise compared with the adaptive background modeling algorithm. The experiment results showed that the proposed algorithm reserved the motion object information well and removed the background to the maximum.
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Jain, Neeraj Kumar, and Singara Singh Kasana. "High-Capacity Reversible Data Hiding Using Modified Pixel Value Ordering Approach." Journal of Circuits, Systems and Computers 27, no. 11 (June 6, 2018): 1850175. http://dx.doi.org/10.1142/s021812661850175x.
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The proposed reversible data hiding technique is the extension of Peng et al.’s technique [F. Peng, X. Li and B. Yang, Improved PVO-based reversible data hiding, Digit. Signal Process. 25 (2014) 255–265]. In this technique, a cover image is segmented into nonoverlapping blocks of equal size. Each block is sorted in ascending order and then differences are calculated on the basis of locations of its largest and second largest pixel values. Negative predicted differences are utilized to create empty spaces which further enhance the embedding capacity of the proposed technique. Also, the already sorted blocks are used to enhance the visual quality of marked images as pixels of these blocks are more correlated than the unsorted pixels of the block. Experimental results show the effectiveness of the proposed technique.
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Hashmani, Manzoor Ahmed, Mehak Maqbool Memon, Kamran Raza, Syed Hasan Adil, Syed Sajjad Rizvi, and Muhammad Umair. "Content-Aware SLIC Super-Pixels for Semi-Dark Images (SLIC++)." Sensors 22, no. 3 (January 25, 2022): 906. http://dx.doi.org/10.3390/s22030906.
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Super-pixels represent perceptually similar visual feature vectors of the image. Super-pixels are the meaningful group of pixels of the image, bunched together based on the color and proximity of singular pixel. Computation of super-pixels is highly affected in terms of accuracy if the image has high pixel intensities, i.e., a semi-dark image is observed. For computation of super-pixels, a widely used method is SLIC (Simple Linear Iterative Clustering), due to its simplistic approach. The SLIC is considerably faster than other state-of-the-art methods. However, it lacks in functionality to retain the content-aware information of the image due to constrained underlying clustering technique. Moreover, the efficiency of SLIC on semi-dark images is lower than bright images. We extend the functionality of SLIC to several computational distance measures to identify potential substitutes resulting in regular and accurate image segments. We propose a novel SLIC extension, namely, SLIC++ based on hybrid distance measure to retain content-aware information (lacking in SLIC). This makes SLIC++ more efficient than SLIC. The proposed SLIC++ does not only hold efficiency for normal images but also for semi-dark images. The hybrid content-aware distance measure effectively integrates the Euclidean super-pixel calculation features with Geodesic distance calculations to retain the angular movements of the components present in the visual image exclusively targeting semi-dark images. The proposed method is quantitively and qualitatively analyzed using the Berkeley dataset. We not only visually illustrate the benchmarking results, but also report on the associated accuracies against the ground-truth image segments in terms of boundary precision. SLIC++ attains high accuracy and creates content-aware super-pixels even if the images are semi-dark in nature. Our findings show that SLIC++ achieves precision of 39.7%, outperforming the precision of SLIC by a substantial margin of up to 8.1%.
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Lv, Z., J. Shi, and Y. Wang. "AN ADAPTIVE MORPHOLOGICAL MEAN FILTER FOR VERY HIGH-RESOLUTION REMOTE SENSING IMAGE PROCESSING." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W7 (September 14, 2017): 1269–74. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w7-1269-2017.
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Very high resolution (VHR) remote sensing imagery can reveal the ground object in greater detail, depicting their color, shape, size and structure. However, VHR also leads much original noise in spectra, and this original noise may reduce the reliability of the classification’s result. This paper presents an Adaptive Morphological Mean Filter (AMMF) for smoothing the original noise of VHR imagery and improving the classification’s performance. AMMF is a shape-adaptive filter which is constructed by detecting gradually the spectral similarity between a kernel-anchored pixel and its contextual pixels through an extension-detector with 8-neighbouring pixels, and the spectral value of the kernel-anchored pixel is instead by the mean of group pixels within the adaptive region. The classification maps based on the AMMF are compared with the classification of VHR images based on the homologous filter processing, such as Mean Filter (MF) and Median Filter(MedF). The experimental results suggest the following: 1) VHR image processed using AMMF can not only preserve the detail information among inter-classes but also smooth the noise within intra-class; 2) The proposed AMMF processing can improve the classification’s performance of VHR image, and it obtains a better visual performance and accuracy while comparing with MF and MedF.
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Singh, Satinderjit. "An Alternate Algorithm for (3x3) Median Filtering of Digital Images." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 2, no. 1 (February 2, 2012): 7–9. http://dx.doi.org/10.24297/ijct.v1i1.6732.
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Median filtering is a commonly used technique in image processing. The main problem of the median filter is its high computational cost (for sorting N pixels, the temporal complexity is O(N·log N), even with the most efficient sorting algorithms). When the median filter must be carried out in real time, the software implementation in general-purpose processorsdoes not usually give good results. This Paper presents an efficient algorithm for median filtering with a 3x3 filter kernel with only about 9 comparisons per pixel using spatial coherence between neighboring filter computations. The basic algorithm calculates two medians in one step and reuses sorted slices of three vertical neighboring pixels. An extension of this algorithm for 2D spatial coherence is also examined, which calculates four medians per step.
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Zhu, Yong Sheng, Chun Tao Bai, Dong Feng Zhou, and Qian Wang. "Fabrication Study on Rectangular Luminous Layer for Field Emission Display Panel." Advanced Materials Research 322 (August 2011): 152–55. http://dx.doi.org/10.4028/www.scientific.net/amr.322.152.
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Using carbon nanotube as field emitter, the field emission display (FED) panel with rectangular luminous layer was fabricated. The etched indium tin oxide (ITO) film was used as the ITO electrodes, and the phosphor powder was prepared to form the phosphor layer, so the rectangular luminous layer was fabricated on the anode back plane. In one anode pixel, the three anode sub-pixels would be included, which would reside on the same ITO electrode surface. The insulation layer would separate the adjacent anode sub-pixels and the adjacent ITO electrode, and the fabricated anode extension line was mainly used to reduce the excessive voltage drop. The FED panel with rectangular luminous layer possessed good field emission characteristic and high image brightness.
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Maiti, Somanka, Ashish Kumar, Smriti Jain, and Gaurav Bhatnagar. "A Novel Image Inpainting Framework Using Regression." ACM Transactions on Internet Technology 21, no. 3 (June 15, 2021): 1–16. http://dx.doi.org/10.1145/3402177.
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In this article, a blockwise regression-based image inpainting framework is proposed. The core idea is to fill the unknown region in two stages: Extrapolate the edges to the unknown region and then fill the unknown pixels values in each sub-region demarcated by the extended edges. Canny edge detection and linear edge extension are used to respectively identify and extend edges to the unknown region followed by regression within each sub-region to predict the unknown pixel values. Two different regression models based on K-nearest neighbours and support vectors machine are used to predict the unknown pixel values. The proposed framework has the advantage of inpainting without requiring prior training on any image dataset. The extensive experiments on different images with contrasting distortions demonstrate the robustness of the proposed framework and a detailed comparative analysis shows that the proposed technique outperforms existing state-of-the-art image inpainting methods. Finally, the proposed techniques are applied to MRI images suffering from susceptibility artifacts to illustrate the practical usage of the proposed work.
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Choudhury, Anustup, and Scott Daly. "Comparing a spatial extension of ICTCP color representation with S-CIELAB and other recent color metrics for HDR and WCG quality assessment." Electronic Imaging 2020, no. 15 (January 26, 2020): 162–1. http://dx.doi.org/10.2352/issn.2470-1173.2020.15.color-123.
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Content created in High Dynamic Range (HDR) and Wide Color Gamut (WCG) is becoming more ubiquitous, driving the need for reliable tools for evaluating the quality across the imaging ecosystem. One of the simplest techniques to measure the quality of any video system is to measure the color errors. The traditional color difference metrics such as ΔE00 and the newer HDR specific metrics such as ΔEZ and ΔEITP compute color difference on a pixel-by-pixel basis which do not account for the spatial effects (optical) and active processing (neural) done by the human visual system. In this work, we improve upon the per-pixel ΔEITP color difference metric by performing a spatial extension similar to what was done during the design of S-CIELAB. We quantified the performance using four standard evaluation procedures on four publicly available HDR and WCG image databases and found that the proposed metric results in a marked improvement with subjective scores over existing per-pixel color difference metrics.
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LI Guang-xin, 李光鑫, 徐抒岩 XU Shu-yan, 吴伟平 WU Wei-ping, 孙天宇 SUN Tian-yu, and 郝伟 HAO Wei. "Extension of Piella pixel-level multiresolution image fusion framework and its algorithm." Optics and Precision Engineering 20, no. 12 (2012): 2773–80. http://dx.doi.org/10.3788/ope.20122012.2773.
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Amelio, Alessia, and Clara Pizzuti. "An Evolutionary Approach for Image Segmentation." Evolutionary Computation 22, no. 4 (December 2014): 525–57. http://dx.doi.org/10.1162/evco_a_00115.
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The paper explores the use of evolutionary techniques in dealing with the image segmentation problem. An image is modeled as a weighted undirected graph, where nodes correspond to pixels, and edges connect similar pixels. A genetic algorithm that uses a fitness function based on an extension of the normalized cut criterion is proposed. The algorithm employs the locus-based representation of individuals, which allows for the partitioning of images without setting the number of segments beforehand. A new concept of nearest neighbor that takes into account not only the spatial location of a pixel, but also the affinity with the other pixels contained in the neighborhood, is also defined. Experimental results show that our approach is able to segment images in a number of regions that conform well to human visual perception. The visual perceptiveness is substantiated by objective evaluation methods based on uniformity of pixels inside a region, and comparison with ground-truth segmentations available for part of the used test images.
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Fernández, Claudio Ignacio, Ata Haddadi, Brigitte Leblon, Jinfei Wang, and Keri Wang. "Comparison between Three Registration Methods in the Case of Non-Georeferenced Close Range of Multispectral Images." Remote Sensing 13, no. 3 (January 24, 2021): 396. http://dx.doi.org/10.3390/rs13030396.
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Cucumber powdery mildew, which is caused by Podosphaera xanthii, is a major disease that has a significant economic impact in cucumber greenhouse production. It is necessary to develop a non-invasive fast detection system for that disease. Such a system will use multispectral imagery acquired at a close range with a camera attached to a mobile cart’s mechanic extension. This study evaluated three image registration methods applied to non-georeferenced multispectral images acquired at close range over greenhouse cucumber plants with a MicaSense® RedEdge camera. The detection of matching points was performed using Speeded-Up Robust Features (SURF), and outliers matching points were removed using the M-estimator Sample Consensus (MSAC) algorithm. Three geometric transformations (affine, similarity, and projective) were considered in the registration process. For each transformation, we mapped the matching points of the blue, green, red, and NIR band images into the red-edge band space and computed the root mean square error (RMSE in pixel) to estimate the accuracy of each image registration. Our results achieved an RMSE of less than 1 pixel with the similarity and affine transformations and of less than 2 pixels with the projective transformation, whatever the band image. We determined that the best image registration method corresponded to the affine transformation because the RMSE is less than 1 pixel and the RMSEs have a Gaussian distribution for all of the bands, but the blue band.
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Szczepański, Marek, and Krystian Radlak. "Digital Path Approach Despeckle Filter for Ultrasound Imaging and Video." Journal of Healthcare Engineering 2017 (2017): 1–13. http://dx.doi.org/10.1155/2017/9271251.
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We propose a novel filtering technique capable of reducing the multiplicative noise in ultrasound images that is an extension of the denoising algorithms based on the concept of digital paths. In this approach, the filter weights are calculated taking into account the similarity between pixel intensities that belongs to the local neighborhood of the processed pixel, which is called a path. The output of the filter is estimated as the weighted average of pixels connected by the paths. The way of creating paths is pivotal and determines the effectiveness and computational complexity of the proposed filtering design. Such procedure can be effective for different types of noise but fail in the presence of multiplicative noise. To increase the filtering efficiency for this type of disturbances, we introduce some improvements of the basic concept and new classes of similarity functions and finally extend our techniques to a spatiotemporal domain. The experimental results prove that the proposed algorithm provides the comparable results with the state-of-the-art techniques for multiplicative noise removal in ultrasound images and it can be applied for real-time image enhancement of video streams.
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Dan, Mai, Meihui Liu, and Feng Gao. "Motion Deblurring for Single-Pixel Spatial Frequency Domain Imaging." Applied Sciences 12, no. 15 (July 23, 2022): 7402. http://dx.doi.org/10.3390/app12157402.
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The single-pixel imaging technique is applied to spatial frequency domain imaging (SFDI) to bring significant performance advantages in band extension and sensitivity enhancement. However, the large number of samplings required can cause severe quality degradations in the measured image when imaging a moving target. This work presents a novel method of motion deblurring for single-pixel SFDI. In this method, the Fourier coefficients of the reflected image are measured by the Fourier single-pixel imaging technique. On this basis, a motion-degradation-model-based compensation, which is derived by the phase-shift and frequency-shift properties of Fourier transform, is adopted to eliminate the effects of target displacements on the measurements. The target displacements required in the method are obtained using a fast motion estimation approach. A series of numerical and experimental validations show that the proposed method can effectively deblur the moving targets and accordingly improves the accuracy of the extracted optical properties, rendering it a potentially powerful way of broadening the clinical application of single-pixel SFDI.
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Gui, Chao, Detian Wang, Xiwang Huang, Chunyan Wu, Xin Chen, and Huachuan Huang. "Super-Resolution and Wide-Field-of-View Imaging Based on Large-Angle Deflection with Risley Prisms." Sensors 23, no. 4 (February 5, 2023): 1793. http://dx.doi.org/10.3390/s23041793.
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A novel single camera combined with Risley prisms is proposed to achieve a super-resolution (SR) imaging and field-of-view extension (FOV) imaging method. We develop a mathematical model to consider the imaging aberrations caused by large-angle beam deflection and propose an SR reconstruction scheme that uses a beam backtracking method for image correction combined with a sub-pixel shift alignment technique. For the FOV extension, we provide a new scheme for the scanning position path of the Risley prisms and the number of image acquisitions, which improves the acquisition efficiency and reduces the complexity of image stitching. Simulation results show that the method can increase the image resolution to the diffraction limit of the optical system for imaging systems where the resolution is limited by the pixel size. Experimental results and analytical verification yield that the resolution of the image can be improved by a factor of 2.5, and the FOV extended by a factor of 3 at a reconstruction factor of 5. The FOV extension is in general agreement with the simulation results. Risley prisms can provide a more general, low-cost, and efficient method for SR reconstruction, FOV expansion, central concave imaging, and various scanning imaging.
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Qiao, Yu, Jincheng Zhu, Chengjiang Long, Zeyao Zhang, Yuxin Wang, Zhenjun Du, and Xin Yang. "CPRAL: Collaborative Panoptic-Regional Active Learning for Semantic Segmentation." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 2 (June 28, 2022): 2108–16. http://dx.doi.org/10.1609/aaai.v36i2.20107.
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Acquiring the most representative examples via active learning (AL) can benefit many data-dependent computer vision tasks by minimizing efforts of image-level or pixel-wise annotations. In this paper, we propose a novel Collaborative Panoptic-Regional Active Learning framework (CPRAL) to address the semantic segmentation task. For a small batch of images initially sampled with pixel-wise annotations, we employ panoptic information to initially select unlabeled samples. Considering the class imbalance in the segmentation dataset, we import a Regional Gaussian Attention module (RGA) to achieve semantics-biased selection. The subset is highlighted by vote entropy and then attended by Gaussian kernels to maximize the biased regions. We also propose a Contextual Labels Extension (CLE) to boost regional annotations with contextual attention guidance. With the collaboration of semantics-agnostic panoptic matching and region-biased selection and extension, our CPRAL can strike a balance between labeling efforts and performance and compromise the semantics distribution. We perform extensive experiments on Cityscapes and BDD10K datasets and show that CPRAL outperforms the cutting-edge methods with impressive results and less labeling proportion.
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Ur Rehman, Hafeez, Mohammad Mazyad Hazzazi, Tariq Shah, Zaid Bassfar, and Dawood Shah. "An Efficient Audio Encryption Scheme Based on Elliptic Curve over Finite Fields." Mathematics 11, no. 18 (September 6, 2023): 3824. http://dx.doi.org/10.3390/math11183824.
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Elliptic curve (EC) based cryptographic systems are more trustworthy than the currently used cryptographic approaches since they require less computational work while providing good security. This paper shows how to use an EC to make a good cryptosystem for encrypting digital audio. As a preliminary step, the system uses an EC of a particular type over a binary extension field to distort the digital audio pixel position. It reduces the inter-correlation between pixels in the original audio, making the system resistant to statistical attacks. In creating confusion in the data, an EC over a binary extension field is used to make a different number of substitution boxes (S-boxes). The suggested design employs a unique curve that relies on efficient EC arithmetic operations in the diffusion module. As a result, it generates high-quality pseudo-random numbers (PRNs) and achieves optimal diffusion in encrypted audio files with less processing work. Audio files of various sizes and kinds can all be encrypted using the provided algorithm. Moreover, the results show that this method effectively protects many kinds of audio recordings and is more resistant to statistical and differential attacks.
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Qu, Zhipeng, Howard W. Barker, Jason N. S. Cole, and Mark W. Shephard. "Across-track extension of retrieved cloud and aerosol properties for the EarthCARE mission: the ACMB-3D product." Atmospheric Measurement Techniques 16, no. 9 (May 4, 2023): 2319–31. http://dx.doi.org/10.5194/amt-16-2319-2023.
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Abstract. The narrow cross section of cloud and aerosol properties retrieved by L2 algorithms that operate on data from EarthCARE's nadir-pointing sensors is broadened across-track by an algorithm that is described and demonstrated here. This scene construction algorithm (SCA) consists of four components. At its core is a radiance-matching procedure that works with measurements made by EarthCARE's Multi-Spectral Imager (MSI). In essence, an off-nadir pixel gets filled with retrieved profiles that are associated with a (nearby) nadir pixel whose MSI radiances best match those of the off-nadir pixel. The SCA constructs a 3D array of cloud and aerosol (and surface) properties for entire frames that measure ∼6000 km along-track by 150 km across-track (i.e., the MSI's full swath). Constructed domains out to ∼15 km across-track on both sides of nadir are used explicitly downstream as input for 3D radiative transfer models that predict top-of-atmosphere (TOA) broadband solar and thermal fluxes and radiances. These quantities are compared to commensurate measurements made by EarthCARE's Broadband Radiometer (BBR), thus facilitating a continuous closure assessment of the retrievals. Three 6000 km ×200 km frames of synthetic EarthCARE observations were used to demonstrate the SCA. The main conclusion is that errors in modelled TOA fluxes that stem from use of 3D domains produced by the SCA are expected to be less than ±5 W m−2 and rarely larger than ±10 W m−2. As such, the SCA, as purveyor of information needed to run 3D radiative transfer models, should help more than hinder the radiative closure assessment of EarthCARE's L2 retrievals.
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Arashiro, E. K. N., J. H. M. Viana, J. F. Fonseca, L. G. B. Siqueira, J. H. Bruschi, L. S. Camargo, C. A. C. Fernandes, and F. Z. Brandao. "313 ASSESSMENT OF LUTEAL FUNCTION IN TOGGENBURG GOATS BY COMPUTER-ASSISTED IMAGE ANALYSIS." Reproduction, Fertility and Development 21, no. 1 (2009): 253. http://dx.doi.org/10.1071/rdv21n1ab313.
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Computer-assisted image analysis is a technological extension of reproductive ultrasonography and allows the quantitative assessment of the luteal echotexture, which is related to changes in histological features and, consequently, to steroidogenesis. The aim of this study was to determine the efficiency of luteal echotexture evaluation as a tool to assess luteal function in different phases of the estrous cycle in Toggenburg goats. Nulliparous goats (n = 21), 8 months in age, 33.52 ± 1.22 kg of body weight, and body score condition of 3.5 ± 0.07 (1 to 5 scale), which showed estrus within a 48-h period during the natural breeding season (March and April), were used. After estrous detection (Day 0) and mating, ovarian sonographic evaluations were performed daily using a portable ultrasound device (Aloka SSD 500, Aloka Co.) equipped with an adapted linear transrectal 5-MHz probe. The examinations were preceded by blood sample collections, which were stored until radioimmunoassay for progesterone (P4). Images were recorded in VHS tapes, then digitized to TIFF files (resolution of 1500 × 1125 pixels) using a video capture board. A representative elementary area of 5625 pixels (0.31 cm2) was defined for the luteal tissue according to the criterion proposed by Van den Bygaart and Protz 1999. Computer-assisted analyses were performed using custom-developed software (Quantporo®). Each pixel received a numeric value ranging from 0 (black) to 255 (white). Luteal echotexture and plasma P4 data were analyzed by ANOVA, and differences among means were determined by Tukey’s test. Correlations were established by Pearson’s correlation method. Results are shown as mean ± SEM. Corpora lutea size increased progressively (P < 0.001) until Day 9, when it reached the maximum area (1.26 ± 0.32 cm2). No increase in size was detected on the subsequent days (P > 0.05). Plasma P4 levels increased until a maximum value on Day 9 (6.31 ± 0.46 ng mL–1), and no increase was observed further (P > 0.05). In nonpregnant animals (n = 7), luteolysis was characterized by an abrupt decrease in plasma P4 concentration, which dropped to values lower than 1 ng mL–1 24 h after the onset of the process, whereas luteal area decreased gradually. Plasma P4 concentration was correlated to luteal area during luteogenesis and luteolysis (r = 0.63 and r = 0.50, respectively; P < 0.05). Mean pixel value showed a progressive increase during luteogenesis and reached the maximum value on Day 13 (54.33 ± 1.83). During corpus luteum (CL) regression, mean pixel value decreased to lower values 48 h after the onset of natural luteolysis (P < 0.05). Through both luteogenesis and luteolysis, positive correlations were observed between mean pixel values and luteal area (r = 0.34 and r = 0.26, respectively; P < 0.05) and also between mean pixel values and plasma P4 concentration (r = 0.24 and r = 0.37, respectively; P < 0.05). Pixel heterogeneity was not correlated to luteal area nor plasma P4 levels. These results suggest an association between CL echotexture and steroidogenic function; therefore, the quantitative assessment of the pixel brightness has a potential to be used for luteal function evaluation in goats. FAPEMIG and CAPES.
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Fidan, Mehmet, and Ömer Nezih Gerek. "Mycielski Based 2d-Predictive Image Coding Algorithm." Applied Mechanics and Materials 850 (August 2016): 144–51. http://dx.doi.org/10.4028/www.scientific.net/amm.850.144.
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The Mycielski method is a prospering prediction algorithm which is based on searching and finding largest repeated binary patterns. It uses infinite-past data to devise a rule based prediction method on a time series. In this work, a novel two-dimensional (image processing) version of the Mycielski algorithm is proposed. Since the dimensionality definition of “past” data increases in two-dimensional signals, the proposed algorithm also needs to handle how the boundaries of the pixel cliques are iteratively extended in the neighborhood of a current pixel. The clique extension invokes novel similarity search strategies that depend on the chosen physical distance metric. The proposed prediction algorithm is used for predictive image compression and performance comparisons with other predictive coding methods are presented.
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Wahyudi, Bagus Prasetyo, Diah Rizqiwati, and Denar Regata Akbi. "Rancang Bangun Aplikasi Enkripsi Citra Berdasarkan Operasi Rotasi." Jurnal Repositor 1, no. 1 (October 8, 2019): 1. http://dx.doi.org/10.22219/repositor.v1i1.2.
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Cryptography is a discipline that uses mathematical equations when doing the decryption process until encryption. This technique uses to convert the initial message into the form of certain codes, in this study using the rotation method, the rotation method itself is the algorithm to rotate the image on its axis in part of the image. Aiming that information stored and sent to the recipient can’t be read or not easily understood by a third party or parties that are not eligible, advantages of the research made is the speed of fast application process and the decline in file size and not easy manual decryption With other tools, the result of encryption application encoding the occurrence of file size that occurs after the decryption process and encryption when compared with the initial size of the image file, and there is no decrease in the size of the file on BMP extension, the speed of encryption time to the file and the pixel size in the image file extension BMP And PNG on 2000x2000 pixel size has the best speed improvement that is equal to 0.12x faster, and change the histogram in the initial image with the result of encryption. This research is built using Python 3.4 programming language, and coupled with Library PIL-pillow, Library Time.
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Gao, Zhiyuan, Suying Yao, Congjie Yang, and Jiangtao Xu. "A Dynamic Range Extension Technique for CMOS Image Sensors With In-Pixel Dual Exposure Synthesis." IEEE Sensors Journal 15, no. 6 (June 2015): 3265–73. http://dx.doi.org/10.1109/jsen.2014.2379942.
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Riza, Nabeel A., and Nazim Ashraf. "Calibration Empowered Minimalistic Multi-Exposure Image Processing Technique for Camera Linear Dynamic Range Extension." Electronic Imaging 2020, no. 7 (January 26, 2020): 213–1. http://dx.doi.org/10.2352/issn.2470-1173.2020.7.iss-213.
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Proposed for the first time is a novel calibration empowered minimalistic multi-exposure image processing technique using measured sensor pixel voltage output and exposure time factor limits for robust camera linear dynamic range extension. The technique exploits the best linear response region of an overall nonlinear response image sensor to robustly recover via minimal count multi-exposure image fusion, the true and precise scaled High Dynamic Range (HDR) irradiance map. CMOS sensor-based experiments using a measured Low Dynamic Range (LDR) 44 dB linear region for the technique with a minimum of 2 multi-exposure images provides robust recovery of 78 dB HDR low contrast highly calibrated test targets.
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PARK, JUN-HYUB, MYUNG-SOO SHIN, DONG-JOONG KANG, SUNG-JO LIM, and JONG-EUN HA. "IMPROVEMENT OF MEASUREMENT ACCURACY OF STRAIN OF THIN FILM BY CCD CAMERA WITH A TEMPLATE MATCHING METHOD USING THE 2ND-ORDER POLYNOMIAL INTERPOLATION." International Journal of Modern Physics B 24, no. 15n16 (June 30, 2010): 3101–6. http://dx.doi.org/10.1142/s021797921006615x.
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In this study, a system for non-contact in-situ measurement of strain during tensile test of thin films by using CCD camera with marking surface of specimen by black pen was implemented as a sensing device. To improve accuracy of measurement when CCD camera is used, this paper proposed a new method for measuring strain during tensile test of specimen with micrometer size. The size of pixel of CCD camera determines resolution of measurement, but the size of pixel can not satisfy the resolution required in tensile test of thin film because the extension of the specimen is very small during the tensile test. To increase resolution of measurement, the suggested method performs an accurate subpixel matching by applying 2nd order polynomial interpolation method to the conventional template matching. The algorithm was developed to calculate location of subpixel providing the best matching value by performing single dimensional polynomial interpolation from the results of pixel-based matching at a local region of image. The measurement resolution was less than 0.01 times of original pixel size. To verify the reliability of the system, the tensile test for the BeNi thin film was performed, which is widely used as a material in micro-probe tip. Tensile tests were performed and strains were measured using the proposed method and also the capacitance type displacement sensor for comparison. It is demonstrated that the new strain measurement system can effectively describe a behavior of materials after yield during the tensile test of the specimen at microscale with easy setup and better accuracy.
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Barazzetti, Luigi, Mattia Previtali, and Marco Scaioni. "Procedures for Condition Mapping Using 360° Images." ISPRS International Journal of Geo-Information 9, no. 1 (January 7, 2020): 34. http://dx.doi.org/10.3390/ijgi9010034.
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The identification of deterioration mechanisms and their monitoring over time is an essential phase for conservation. This work aimed at developing a novel approach for deterioration mapping and monitoring based on 360° images, which allows for simple and rapid data collection. The opportunity to capture the whole scene around a 360° camera reduces the number of images needed in a condition mapping project, resulting in a powerful solution to document small and narrow spaces. The paper will describe the implemented workflow for deterioration mapping based on 360° images, which highlights pathologies on surfaces and quantitatively measures their extension. Such a result will be available as standard outputs as well as an innovative virtual environment for immersive visualization. The case of multi-temporal data acquisition will be considered and discussed as well. Multiple 360° images acquired at different epochs from slightly different points are co-registered to obtain pixel-to-pixel correspondence, providing a solution to quantify and track deterioration effects.
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Wang, Hong-Yuan, and Fuhua Chen. "Semisupervised Soft Mumford-Shah Model for MRI Brain Image Segmentation." Applied Computational Intelligence and Soft Computing 2016 (2016): 1–14. http://dx.doi.org/10.1155/2016/8508329.
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One challenge of unsupervised MRI brain image segmentation is the central gray matter due to the faint contrast with respect to the surrounding white matter. In this paper, the necessity of supervised image segmentation is addressed, and a soft Mumford-Shah model is introduced. Then, a framework of semisupervised image segmentation based on soft Mumford-Shah model is developed. The main contribution of this paper lies in the development a framework of a semisupervised soft image segmentation using both Bayesian principle and the principle of soft image segmentation. The developed framework classifies pixels using a semisupervised and interactive way, where the class of a pixel is not only determined by its features but also determined by its distance from those known regions. The developed semisupervised soft segmentation model turns out to be an extension of the unsupervised soft Mumford-Shah model. The framework is then applied to MRI brain image segmentation. Experimental results demonstrate that the developed framework outperforms the state-of-the-art methods of unsupervised segmentation. The new method can produce segmentation as precise as required.
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Zhang, Wei-Tao, Sheng-Di Zheng, Yi-Bang Li, Jiao Guo, and Hui Wang. "A Full Tensor Decomposition Network for Crop Classification with Polarization Extension." Remote Sensing 15, no. 1 (December 22, 2022): 56. http://dx.doi.org/10.3390/rs15010056.
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The multisource data fusion technique has been proven to perform better in crop classification. However, traditional fusion methods simply stack the original source data and their corresponding features, which can be only regarded as a superficial fusion method rather than deep fusion. This paper proposes a pixel-level fusion method for multispectral data and dual polarimetric synthetic aperture radar (PolSAR) data based on the polarization extension, which yields synthetic quad PolSAR data. Then we can generate high-dimensional features by means of various polarization decomposition schemes. High-dimensional features usually cause the curse of the dimensionality problem. To overcome this drawback in crop classification using the end-to-end network, we propose a simple network, namely the full tensor decomposition network (FTDN), where the feature extraction in the hidden layer is accomplished by tensor transformation. The number of parameters of the FTDN is considerably fewer than that of traditional neural networks. Moreover, the FTDN admits higher classification accuracy by making full use of structural information of PolSAR data. The experimental results demonstrate the effectiveness of the fusion method and the FTDN model.
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Flatt, H., A. Tarnowsky, H. Blume, and P. Pirsch. "Hardware-Abbildung eines videobasierten Verfahrens zur echtzeitfähigen Auswertung von Winkelhistogrammen auf eine modulare Coprozessor-Architektur." Advances in Radio Science 8 (October 1, 2010): 135–42. http://dx.doi.org/10.5194/ars-8-135-2010.
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Abstract. Dieser Beitrag behandelt die Abbildung eines videobasierten Verfahrens zur echtzeitfähigen Auswertung von Winkelhistogrammen auf eine modulare Coprozessor-Architektur. Die Architektur besteht aus mehreren dedizierten Recheneinheiten zur parallelen Verarbeitung rechenintensiver Bildverarbeitungsverfahren und ist mit einem RISC-Prozessor verbunden. Eine konfigurierbare Architekturerweiterung um eine Recheneinheit zur Auswertung von Winkelhistogrammen von Objekten ermöglicht in Verbindung mit dem RISC eine echtzeitfähige Klassifikation. Je nach Konfiguration sind für die Architekturerweiterung auf einem Xilinx Virtex-5-FPGA zwischen 3300 und 12 000 Lookup-Tables erforderlich. Bei einer Taktfrequenz von 100 MHz können unabhängig von der Bildauflösung pro Einzelbild in einem 25-Hz-Videodatenstrom bis zu 100 Objekte der Größe 256×256 Pixel analysiert werden. This paper presents the mapping of a video-based approach for real-time evaluation of angular histograms on a modular coprocessor architecture. The architecture comprises several dedicated processing elements for parallel processing of computation-intensive image processing tasks and is coupled with a RISC processor. A configurable architecture extension, especially a processing element for evaluating angular histograms of objects in conjunction with a RISC processor, provides a real-time classification. Depending on the configuration of the architecture extension, 3 300 to 12 000 look-up tables are required for a Xilinx Virtex-5 FPGA implementation. Running at a clock frequency of 100 MHz and independently of the image resolution per frame, 100 objects of size 256×256 pixels are analyzed in a 25 Hz video stream by the architecture.
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Scarmana, G. "A METHOD FOR REVERSING THE EFFECT OF DIGITAL IMAGE BLURRING: A SPACE DOMAIN INVESTIGATION." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLVIII-1/W1-2023 (May 25, 2023): 431–35. http://dx.doi.org/10.5194/isprs-archives-xlviii-1-w1-2023-431-2023.
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Abstract. Mobile mapping technology has transformed the way in which we capture and map our surroundings. The widespread use of mobile devices such as smart phones and drones has made data collection more efficient and accessible than ever before. However, the image quality of this data is often compromised due to the static or motion blurs resulting from the device being stationary or moving during the data collection process. This can lead to a loss of information, making the data less useful.To address this issue, an inverse filtering or deblurring method based on the theory of least squares is examined. This method implements a deconvolution process in the space domain and can restore the original image with a high degree of accuracy if the model of the function or filter that blurred the image is known or can be established.The accuracy and validity of the deblurring results are presented in terms of the root mean square error (RMSE) of the differences of pixel intensity values between the original and de-blurred images. In tests using grey-scale aerial images of varying entropies and different types of blurring, the RMSE value never exceeded ±5 pixel intensity values. This discrepancy is due to the rounding of pixel values resulting from image operations.The deblurring method presented in this work is an adaptation and extension of a previously described process, tailored specifically for filtering and restoring images - particularly aerial imagery - affected by static and motion blur. This process could also be applied in image compression processes and techniques of transmission over digital links, where blurring filters can suppress noise and increase the dependence between neighbouring pixel values, thereby improving the compression ratio (CR).
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Hocking, L. Robert, Thomas Holding, and Carola-Bibiane Schönlieb. "Analysis of Artifacts in Shell-Based Image Inpainting: Why They Occur and How to Eliminate Them." Foundations of Computational Mathematics 20, no. 6 (March 16, 2020): 1549–651. http://dx.doi.org/10.1007/s10208-020-09450-3.
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AbstractIn this paper we study a class of fast geometric image inpainting methods based on the idea of filling the inpainting domain in successive shells from its boundary inwards. Image pixels are filled by assigning them a color equal to a weighted average of their already filled neighbors. However, there is flexibility in terms of the order in which pixels are filled, the weights used for averaging, and the neighborhood that is averaged over. Varying these degrees of freedom leads to different algorithms, and indeed the literature contains several methods falling into this general class. All of them are very fast, but at the same time all of them leave undesirable artifacts such as “kinking” (bending) or blurring of extrapolated isophotes. Our objective in this paper is to build a theoretical model in order to understand why these artifacts occur and what, if anything, can be done about them. Our model is based on two distinct limits: a continuum limit in which the pixel width $$h \rightarrow 0$$ h → 0 and an asymptotic limit in which $$h > 0$$ h > 0 but $$h \ll 1$$ h ≪ 1 . The former will allow us to explain “kinking” artifacts (and what to do about them) while the latter will allow us to understand blur. Both limits are derived based on a connection between the class of algorithms under consideration and stopped random walks. At the same time, we consider a semi-implicit extension in which pixels in a given shell are solved for simultaneously by solving a linear system. We prove (within the continuum limit) that this extension is able to completely eliminate kinking artifacts, which we also prove must always be present in the direct method. Finally, we show that although our results are derived in the context of inpainting, they are in fact abstract results that apply more generally. As an example, we show how our theory can also be applied to a problem in numerical linear algebra.
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Afroj, Kamila, and K. Siddique-e. Rabbani. "An Image Smearing Technique to Improve Pigeon Hole Imaging (PHI)." Bangladesh Journal of Medical Physics 4, no. 1 (April 19, 2013): 11–20. http://dx.doi.org/10.3329/bjmp.v4i1.14673.
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This new imaging modality arises as an extension of the 6-electrode Focused Impedance Method (FIM) developed in our laboratory earlier. Current is driven through two concentric pairs of orthogonally placed electrodes while several potential electrodes are located along a diagonal centrally. Through a combination of current drives and potential measurements across adjacent diagonal electrodes, it is possible to obtain admittance sums along the rows and columns of a square matrix formed by these diagonally placed potential electrodes. Through simple backprojection along the rows and columns it is possible to reconstruct a crude image in a square matrix form. Due to its resemblance, the name Pigeon Hole Imaging (PHI) has been coined. The concept has been experimentally tested to identify the location of a single target object in a background of uniform conductivity in 2D and 3D phantoms, in 2x2 and 6x6 matrix formations respectively. Taking the highest pixel to represent the object position the images were correct in all the pixels of the 2x2 image but in only 16 of the 36 pixels adjacent to the diagonal electrodes in the 6x6 image. However, a systematic pattern of image shift was observed in most of the other pixels in the latter, based on which a set of rules were made to correct the image in another 14 pixels. Thus excepting the furthest 6 pixels, correct image could be obtained in all 30 pixels. Thus PHI will be useful in locating exact positions of single target objects simply. DOI: http://dx.doi.org/10.3329/bjmp.v4i1.14673 Bangladesh Journal of Medical Physics Vol.4 No.1 2011 11-20
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Pan, Shanjen, Wenshan Liou, Ang Shih, Mun-Soo Park, Ge Wang, Sterling P. Newberry, Hyogun Kim, Doug M. Shinozaki, and Ping-Chin Cheng. "Experimental System for X-ray Cone-Beam Microtomography." Microscopy and Microanalysis 4, no. 1 (February 1998): 56–62. http://dx.doi.org/10.1017/s1431927698980059.
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A laboratory test of X-ray tomography employing a diverging beam of X-rays rather than the usual parallel X-ray beam is described. We chose to test and demonstrate the advantages of divergent beam tomography by imaging an extracted juvenile human premolar using an ordinary dental X-ray source and a cooled CCD camera. Experiments with a three-piece cover-glass sample and with the human tooth demonstrated that three-dimensional reconstruction can be achieved at 34 μm per pixel resolution employing an X-ray tube spot 800 μm in its smallest direction without requiring close contact with the fluorescent screen. Reconstruction of a 256 x 256 pixel single-plane image from 100 projection images took only 45 sec on a personal computer with a Pentium 166 MHz processor. We have also demonstrated a volume reconstruction of 256 x 256 x 256 voxels from the data. Successful extension of this work to submicrometer projection X-ray microscopy is predicted. Improved resolution of medical tomography is another possible application.
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Bhandari, Vijay, Sitendra Tamarkar, and Piyush Shukla. "Development of Efficient and Secure Image Transposal Algorithm using 16 *16 Truncation Table." International Journal of Advance Research and Innovation 6, no. 4 (2018): 60–68. http://dx.doi.org/10.51976/ijari.641808.
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In later a long time, different mystery sharing plans for computerized pictures have been created in arrange to advance statement security. Past strategies in the writing have made endeavours efforts endeavours to accomplish the merits properties for a great mystery picture transposing such as execute (k,n) limit, basic recuperation, no pixel development, the produced covert pictureare important, the arrange of pictures is elective and lossless recuperation of the mystery image. To the leading of our information, no past mystery sharing scheme accomplishes all the over properties with great quality of important pictures. In this paper, we proposed puzzle picture montages based on data stowing away hypothesis to make strides the quality of important pictures with lower computation and great expansibility. In the light of, the proposed plans have the important points of lossless and elective arrange recuperation and no pixel development expansion extension development. This is observing with past advance appear the execution of the planned conspires. The calculations displayed permit distinctive aligned of protection for the data covered up in the covering-document.
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Gong, Sui, and Timothy Newman. "Isocontouring with sharp corner features." Machine Graphics and Vision 27, no. 1/4 (December 1, 2019): 21–46. http://dx.doi.org/10.22630/mgv.2018.27.1.2.
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A method that achieves closed boundary finding in images (including slice images) with sub-pixel precision while enabling expression of sharp corners in that boundary is described. The method is a new extension to the well-known Marching Squares (MS) 2D isocontouring method that recovers sharp corner features that MS usually recovers as chamfered. The method has two major components: (1) detection of areas in the input image likely to contain sharp corner features, and (2) examination of image locations directly adjacent to the area with likely corners. Results of applying the new method, as well as its performance analysis, are also shown.
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Garcia-Dorado, D., P. Theroux, M. Desco, J. Solares, J. Elizaga, F. Fernandez-Aviles, J. Alonso, and J. Soriano. "Cell-to-cell interaction: a mechanism to explain wave-front progression of myocardial necrosis." American Journal of Physiology-Heart and Circulatory Physiology 256, no. 5 (May 1, 1989): H1266—H1273. http://dx.doi.org/10.1152/ajpheart.1989.256.5.h1266.
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Histological sections performed 24 h after coronary occlusion in eight pigs displayed compact infarcts extending transmurally with well-defined edges; reconstruction and inspection of the area of necrosis showed a geometric distribution of the infarcts with very irregular, interdigitating edges always in continuity with the main mass of necrosis. Reperfusion in 32 pigs after periods of coronary occlusion of 90, 60, 45, and 30 min exponentially reduced infarct size and transmural extension of the infarct but did not modify its geometry. The two-dimensional size, progression, and geometry of the infarcts could be reproduced by a computer model. In the simulated infarcts, each myocardial cell within the area at risk was represented by a pixel. The algorithm included an inner loop, which determined at random at each iteration a status of reversible or irreversible damage to all pixels. The number of iterations could reproduce infarct of various sizes. With the addition of an index of transmural sensitivity to ischemia, progression of the infarct area could also be reproduced. The only possible means of reproducing the geometry of the infarct was to enter into the program a contiguity condition requiring a direct contact between irreversibly damaged pixels. These observations suggest that the physical interaction between cells is an important determinant of progression of necrosis during coronary occlusion.
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Lin, Yi-Tun, and Graham D. Finlayson. "A Rehabilitation of Pixel-Based Spectral Reconstruction from RGB Images." Sensors 23, no. 8 (April 21, 2023): 4155. http://dx.doi.org/10.3390/s23084155.
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Recently, many deep neural networks (DNN) have been proposed to solve the spectral reconstruction (SR) problem: recovering spectra from RGB measurements. Most DNNs seek to learn the relationship between an RGB viewed in a given spatial context and its corresponding spectra. Significantly, it is argued that the same RGB can map to different spectra depending on the context with respect to which it is seen and, more generally, that accounting for spatial context leads to improved SR. However, as it stands, DNN performance is only slightly better than the much simpler pixel-based methods where spatial context is not used. In this paper, we present a new pixel-based algorithm called A++ (an extension of the A+ sparse coding algorithm). In A+, RGBs are clustered, and within each cluster, a designated linear SR map is trained to recover spectra. In A++, we cluster the spectra instead in an attempt to ensure neighboring spectra (i.e., spectra in the same cluster) are recovered by the same SR map. A polynomial regression framework is developed to estimate the spectral neighborhoods given only the RGB values in testing, which in turn determines which mapping should be used to map each testing RGB to its reconstructed spectrum. Compared to the leading DNNs, not only does A++ deliver the best results, it is parameterized by orders of magnitude fewer parameters and has a significantly faster implementation. Moreover, in contradistinction to some DNN methods, A++ uses pixel-based processing, which is robust to image manipulations that alter the spatial context (e.g., blurring and rotations). Our demonstration on the scene relighting application also shows that, while SR methods, in general, provide more accurate relighting results compared to the traditional diagonal matrix correction, A++ provides superior color accuracy and robustness compared to the top DNN methods.
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Jo, Sung-Hyun, Hee Ho Lee, Myunghan Bae, Minho Lee, Ju-Yeong Kim, Pyung Choi, and Jang-Kyoo Shin. "Extension of the Dynamic Range in the CMOS Active Pixel Sensor Using a Stacked Photodiode and Feedback Structure." Journal of Sensor Science and Technology 22, no. 4 (July 31, 2013): 256–61. http://dx.doi.org/10.5369/jsst.2013.22.4.256.
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Zhang, Yuchao, Ronghua Ma, Hongtao Duan, Steven Loiselle, and Jinduo Xu. "Satellite analysis to identify changes and drivers of CyanoHABs dynamics in Lake Taihu." Water Supply 16, no. 5 (April 27, 2016): 1451–66. http://dx.doi.org/10.2166/ws.2016.074.
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A long-term satellite-based analysis was performed to assess the impact of environmental factors on cyanobacterial harmful blooms (CyanoHABs) dynamics in a typical shallow lake, Lake Taihu. A sub-pixel approach (algae pixel-growing algorithm) was used with 13 years of MOderate-resolution Imaging Spectroradiometer (MODIS) data to evaluate changes in bloom extension, initiation date, duration, and occurrence frequency before and after a massive bloom event (2007). Results indicated that the conditions after this event changed, with a general delay in bloom initiation and a reduction in bloom duration. The environmental drivers of daily, monthly and inter-annual CyanoHABs dynamics were analyzed by detrended correspondence analysis, principal components analysis and redundancy analysis. This demonstrated that wind speed was the main driver for daily CyanoHABs dynamics, and CODmn, total phosphorus and water temperature were closely related to monthly CyanoHABs dynamics. For the year scale, Tmean and nutrients were the main drivers of CyanoHABs initiation date and duration, and meteorological factors influenced CyanoHABs frequency for the whole lake. Regular monitoring of CyanoHABs by remote sensing has become a key element in the continued assessment of bloom conditions in Lake Taihu, and nutrient reduction policies contribute to decrease CyanoHABs occurrence.
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Xi, Jingke, and Shukun Ran. "Quantum image K-nearest neighbor mean filtering." Quantum Information and Computation 23, no. 1&2 (January 2023): 45–66. http://dx.doi.org/10.26421/qic23.1-2-4.
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Quantum image filtering is an extension of classical image filtering algorithms, which mainly studies image filtering models based on quantum characteristics. The existing quantum image filtering focuses on noise detection and noise suppression, ignoring the effect of filtering on image boundaries. In this paper, a new quantum image filtering algorithm is proposed to realize the K-nearest neighbor mean filtering task, which can achieve the purpose of boundary preservation while suppressing noise. The main work includes: a new quantum compute module for calculating the absolute value of the difference between two non-negative integers is proposed, thus constructing the quantum circuit of the distance calculation module for calculating the grayscale distance between the neighborhood pixels and the center pixel; the existing quantum sorting module is improved to sort the neighborhood pixels with the distance as the sorting condition, and thus the quantum circuit of the K-nearest neighbor extraction module is constructed; the quantum circuit of the K-nearest neighbor mean calculation module is designed to calculate the gray mean of the selected neighbor pixels; finally, a complete quantum circuit of the proposed quantum image filtering algorithm is constructed, and carried out the image de-noising simulation experiment. The relevant experimental indicators show that the quantum image K-nearest neighbor mean filtering algorithm has the same effect on image noise suppression as the classical K-nearest neighbor mean filtering algorithm, but the time complexity of this method is reduced from $O\left(2^{2 n}\right)$ of the classical algorithm to $O\left(n^{2}+q^{2}\right)$.
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Vargic, Radoslav, and Jaroslav Polec. "Hierarchical mask creation for intelligent image coding using saliency maps." International Journal of Advances in Telecommunications, Electrotechnics, Signals and Systems 5, no. 3 (December 20, 2016): 155. http://dx.doi.org/10.11601/ijates.v5i3.191.
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In this paper we analyze basic mask creation methods for intelligent image coding using saliency maps. For saliency maps based image coding we use specific extension of SPIHT algorithm called SM SPIHT related to region of interest encoding but extending this approach further, ending with individual weight of importance for each pixel in image using the form of saliency map. This approach is proved to be effective. In this article we analyze impact of different basic hierarchical mask creation methods, which have impact on error separation between salient and not salient parts of the image. The results indicate that proposed mask creation method outperforms JPEG2000 based mask tree creation method.
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Burns, Nicholas, Aly Rahemtulla, Scott Annett, Beatriz Moreno, and Stefan Kycia. "An inclined detector geometry for improved X-ray total scattering measurements." Journal of Applied Crystallography 56, no. 2 (April 1, 2023): 510–18. http://dx.doi.org/10.1107/s1600576723001747.
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X-ray total scattering measurements are implemented using a digital flat-panel area detector in an inclined geometry and compared with the traditional geometry. The traditional geometry is defined here by the incident X-ray beam impinging on and normal to the center-most pixel of a detector. The inclined geometry is defined here by a detector at a pitch angle α, set to 15° in this case, bisected by the vertical scattering plane. The detector is positioned such that the incident X-ray beam strikes the pixels along the bottom edge and 90° scattered X-rays impinge on the pixels along the top edge. The geometric attributes of the inclined geometry translate into multiple benefits, such as an extension of the measurable scattering range to 90°, a 47% increase in the accessible magnitudes of the reciprocal-space vector Q and a leveling of the dynamic range in the measured total scattering pattern. As a result, a sixfold improvement in signal-to-noise ratios is observed at higher scattering angles, enabling up to a 36-fold reduction in acquisition time. Additionally, the extent of applied modification functions is reduced, decreasing the magnitude of termination ripples and improving the real-space resolution of the pair distribution function G(r). Taken all together, these factors indicate that the inclined geometry produces higher quality data than the traditional geometry, usable for simultaneous Rietveld refinement and total scattering studies.
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Rocha, Davi Marcondes, Lúcia Helena Pereira Nóbrega, Maria de Fátima Zorato, Vitor Alex Alves de Marchi, and Arlete Teresinha Beuren. "Classification and Pixel-Based Segmentation to Evaluate Soybean Seeds Submitted to Tetrazolium Test." Journal of Agricultural Science 11, no. 13 (August 15, 2019): 186. http://dx.doi.org/10.5539/jas.v11n13p186.
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Production and use of high quality seeds are essential for the soybean crop. Thus, the quality control system in seeds industry must be reliable, precise, and fast. Tetrazolium test evaluates not only seeds viability but also their vigor, as well as provides information concerning agents that cause their quality reduction. Although this test does not use expensive devices and reagents, it requires a well-trained analyst. Its precision depends on knowledge of all techniques and required procedures. Besides, also necessary is the observer’s subjectivity. So, this trial aimed at developing a computational tool that could minimize the implicit subjectivity in carrying out this test. It also contributes to generate a greater credibility of information and to guarantee precise answers. Algorithms of supervised classification were applied based on extraction of digital images characterization of tetrazolium test. This procedure aimed at producing pixel-based segmentation of those images, to produce a digital segmented image of tetrazolium test according to damage classes. This tool allows, based on image of tetrazolium test, to identify damage on soybean embryos, as well as its site and extension on tissues, so that the interpretation is less subjective. The applied method allowed identifying damage on images of tetrazolium tests in a straightforward way, as well as extracting safer information about those damages and carrying out management control of tetrazolium test according to a seed data file.
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Aguilar-González, Abiel, Miguel Arias-Estrada, and François Berry. "Depth from a Motion Algorithm and a Hardware Architecture for Smart Cameras." Sensors 19, no. 1 (December 23, 2018): 53. http://dx.doi.org/10.3390/s19010053.
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Applications such as autonomous navigation, robot vision, and autonomous flying require depth map information of a scene. Depth can be estimated by using a single moving camera (depth from motion). However, the traditional depth from motion algorithms have low processing speeds and high hardware requirements that limit the embedded capabilities. In this work, we propose a hardware architecture for depth from motion that consists of a flow/depth transformation and a new optical flow algorithm. Our optical flow formulation consists in an extension of the stereo matching problem. A pixel-parallel/window-parallel approach where a correlation function based on the sum of absolute difference (SAD) computes the optical flow is proposed. Further, in order to improve the SAD, the curl of the intensity gradient as a preprocessing step is proposed. Experimental results demonstrated that it is possible to reach higher accuracy (90% of accuracy) compared with previous Field Programmable Gate Array (FPGA)-based optical flow algorithms. For the depth estimation, our algorithm delivers dense maps with motion and depth information on all image pixels, with a processing speed up to 128 times faster than that of previous work, making it possible to achieve high performance in the context of embedded applications.