Journal articles on the topic 'Multi channel restoration'
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PAI, Hung-Ta, Alan C. BOVIK, and Brian L. EVANS. "Multi-Channel Blind Image Restoration." Turkish Journal of Electrical Engineering and Computer Sciences 5, no. 1 (January 1, 1997): 79–97. http://dx.doi.org/10.55730/1300-0632.3773.
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Kong, Yanfen, Caiyue Zhou, Chuanyong Zhang, Lin Sun, and Chongbo Zhou. "Multi-Color Channels Based Group Sparse Model for Image Restoration." Algorithms 15, no. 6 (May 24, 2022): 176. http://dx.doi.org/10.3390/a15060176.
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The group sparse representation (GSR) model combines local sparsity and nonlocal similarity in image processing, and achieves excellent results. However, the traditional GSR model and all subsequent improved GSR models convert the RGB space of the image to YCbCr space, and only extract the Y (luminance) channel of YCbCr space to change the color image to a gray image for processing. As a result, the image processing process cannot be loyal to each color channel, so the repair effect is not ideal. A new group sparse representation model based on multi-color channels is proposed in this paper. The model processes R, G and B color channels simultaneously when processing color images rather than processing a single color channel and then combining the results of different channels. The proposed multi-color-channels-based GSR model is compared with state-of-the-art methods. The experimental contrast results show that the proposed model is an effective method and can obtain good results in terms of objective quantitative metrics and subjective visual effects.
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EL-KHAMY, S. E., E. M. SAAD, M. M. HADHOUD, M. I. DESSOUKY, A. M. ABBAS, and F. E. ABD EL-SAMIE. "A MODIFIED WIENER FILTER FOR MULTI-FRAME RESTORATION OF BLURRED AND NOISY IMAGES." International Journal of Information Acquisition 02, no. 02 (June 2005): 123–35. http://dx.doi.org/10.1142/s0219878905000490.
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This paper proposes the use of a modified Wiener digital restoration technique for multi-frame image sequences that are degraded by both blur and noise. The proposed multi-channel Wiener restoration filter accounts for both intra-frame (spatial) and inter-frame (temporal) correlation. A modified cross-correlation formula between consecutive frames, which directly utilizes the motion vectors in the calculation of correlation among frames is derived and implemented in a multi-frame Wiener filter. Our modification estimates the motion vectors (horizontal and vertical) between consecutive frames using the three-step method, and then uses the estimated motion vectors to modify the cross-correlation terms in the formula for restoration. The performed simulations verified that the multi-frame restoration algorithm, that uses the motion information among different frames in restoration, gives improved results than both of the single frame independent restoration and the multi-channel restoration without considering the motion vectors.
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Li, Sanqian, Binjie Qin, Jing Xiao, Qiegen Liu, Yuhao Wang, and Dong Liang. "Multi-Channel and Multi-Model-Based Autoencoding Prior for Grayscale Image Restoration." IEEE Transactions on Image Processing 29 (2020): 142–56. http://dx.doi.org/10.1109/tip.2019.2931240.
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Zhang, Minghui, Yuan Yuan, Fengqin Zhang, Siyuan Wang, Shanshan Wang, and Qiegen Liu. "Multi-Noise and Multi-Channel Derived Prior Information for Grayscale Image Restoration." IEEE Access 7 (2019): 150082–92. http://dx.doi.org/10.1109/access.2019.2946994.
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Tan, Lu, Wanquan Liu, and Zhenkuan Pan. "Color image restoration and inpainting via multi-channel total curvature." Applied Mathematical Modelling 61 (September 2018): 280–99. http://dx.doi.org/10.1016/j.apm.2018.04.017.
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Yang, Huizhen, Songheng Li, Jinlong Liu, Xue Han, and Zhiguang Zhang. "Multi-Channel Blind Restoration of Mixed Noise Images under Atmospheric Turbulence." Atmosphere 13, no. 11 (November 5, 2022): 1842. http://dx.doi.org/10.3390/atmos13111842.
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The imaging quality of astronomical or space objects is significantly degraded by atmospheric turbulence, photon noise, image sensor noise, and other factors. A multi-channel alternating minimization (MCAM) method is proposed to restore degraded images, in which multiple blurred images at different times are selected, and the imaging object and the point spread function are reconstructed alternately. Results show that the restoration index can converge rapidly after two iterations of the MCAM method when six different images are adopted. According to the analysis of the structure similarity index, the stronger the influence of turbulence and mixed noise, the higher the degree of image improvement. The above results can provide a reference for blind restoration of images degraded by atmospheric turbulence and mixed noises.
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Zhu, Min Yun, Feng Su, and Wu Jing Li. "Improved Multi-Scale Retinex Approaches for Color Image Enhancement." Applied Mechanics and Materials 39 (November 2010): 32–37. http://dx.doi.org/10.4028/www.scientific.net/amm.39.32.
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In this paper, an improved multi-scale Retinex with color restoration is proposed by correcting some distortion on color rendition. By using the proposed method, results of image enhancement are obtained and compared further with those acquired by employing the single-scale Retinex, the multi-scale Retinex and the conventional multi-scale Retinex with color restoration. For HSV space shows better color channel independence by comparison with RGB space, a multi-scale Retinex in HSV space is given out and explored to enhance images. The experimental results do show distinct information and effects.
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NAGALI, ELEONORA, FABIO SCIARRINO, FRANCESCO DE MARTINI, MIROSLAV GAVENDA, and RADIM FILIP. "EXPERIMENTAL ENTANGLEMENT RESTORATION ON NOISY CHANNELS BY MEASURING ENVIRONMENT." International Journal of Quantum Information 07, supp01 (January 2009): 1–8. http://dx.doi.org/10.1142/s0219749909004918.
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In the last years, different procedures have been developed in order to recover entanglement after propagation over a noisy channel. However, above a certain amount of noise, entanglement is completely lost. In this case the channel is called "entanglement-breaking" and any multi-copy distillation methods cannot help to reveal even a bit of entanglement. We report the experimental realization of a new protocol which restores entanglement from a single photon entanglement-breaking channel by measuring the information leaking out into the environment. Such restoration entanglement procedure provides new elements to overcome decoherence effects, a subject of renowed interest in quantum communication in the last decade.
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Fateh, Rachid, Anouar Darif, and Said Safi. "Performance Evaluation of MC-CDMA Systems with Single User Detection Technique using Kernel and Linear Adaptive Method." Journal of Telecommunictions and Information Technology 4, no. 2021 (December 30, 2021): 1–11. http://dx.doi.org/10.26636/jtit.2021.151621.
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Among all the techniques combining multi-carrier modulation and spread spectrum, the multi-carrier code division multiple access (MC-CDMA) system is by far the most widely studied. In this paper, we present the performance of the MC-CDMA system associated with key single-user detection techniques. We are interested in problems related to identification and equalization of mobile radio channels, using the kernel method in Hilbert space with a reproducing kernel, and a linear adaptive algorithm, for MC-CDMA systems. In this context, we tested the efficiency of these algorithms, considering practical frequency selective fading channels, called broadband radio access network (BRAN), standardized for MC-CDMA systems. As far as the equalization problem encountered after channel identification is concerned, we use the orthogonality restoration combination (ORC) and the minimum mean square error (MMSE) equalizer techniques to correct the distortion of the channel. Simulation results demonstrate that the kernel algorithm is efficient for practical channels.
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SHIGAKI, KENTA. "MULTI-CHANNEL MEASUREMENTS OF LIGHT VECTOR MESONS AT PHENIX." International Journal of Modern Physics E 16, no. 07n08 (August 2007): 2154–59. http://dx.doi.org/10.1142/s0218301307007611.
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The PHENIX experiment at RHIC is uniquely suitable for systematic studies of light vector mesons, whose mass states are considered as a sensitive probe of partial chiral symmetry restoration and as a signature of deconfined partonic state of matter. Their challengingly small signal to background ratios in multi body decay channels in heavy ion collisions have been extensively attacked. Significant improvements have been recently achieved of signal extraction techniques. The final results on yields, transverse momentum spectra, and possibly mass states of light vector mesons including φ and ω are well in the near future prospects.
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Hashemi Noshahr, Fereidoon, Morteza Nabavi, and Mohamad Sawan. "Multi-Channel Neural Recording Implants: A Review." Sensors 20, no. 3 (February 7, 2020): 904. http://dx.doi.org/10.3390/s20030904.
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The recently growing progress in neuroscience research and relevant achievements, as well as advancements in the fabrication process, have increased the demand for neural interfacing systems. Brain–machine interfaces (BMIs) have been revealed to be a promising method for the diagnosis and treatment of neurological disorders and the restoration of sensory and motor function. Neural recording implants, as a part of BMI, are capable of capturing brain signals, and amplifying, digitizing, and transferring them outside of the body with a transmitter. The main challenges of designing such implants are minimizing power consumption and the silicon area. In this paper, multi-channel neural recording implants are surveyed. After presenting various neural-signal features, we investigate main available neural recording circuit and system architectures. The fundamental blocks of available architectures, such as neural amplifiers, analog to digital converters (ADCs) and compression blocks, are explored. We cover the various topologies of neural amplifiers, provide a comparison, and probe their design challenges. To achieve a relatively high SNR at the output of the neural amplifier, noise reduction techniques are discussed. Also, to transfer neural signals outside of the body, they are digitized using data converters, then in most cases, the data compression is applied to mitigate power consumption. We present the various dedicated ADC structures, as well as an overview of main data compression methods.
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Abd Elghafar, Samir, Salaheldin M. Diab, Bassiouny M. Sallam, Moawad I. Dessouky, El-Sayed M. El-Rabaie, and Fathi E. Abd El-Samie. "Multi-carrier Equalization by Restoration of RedundancY (MERRY) for Adaptive Channel Shortening in Multi-carrier Systems." International Journal of Network Security & Its Applications 5, no. 6 (November 30, 2013): 65–74. http://dx.doi.org/10.5121/ijnsa.2013.5606.
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Guryleva, Anastasiya V., Alexei M. Khorokhorov, and Vitaly S. Kobozev. "Methods Of Increasing Spectral Resolution Of Imaging Spectrometers Built On The Basis Of Multi–channel Radiation Detectors." Volume 28, Number 6, 2020, no. 03-2020 (December 2020): 95–104. http://dx.doi.org/10.33383/2019-098.
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The article proposes the methods of object shooting by means of a spectrometer based on a multi-channel radiation detector and further processing of its results allowing spectral resolution of such spectrometers significantly to increase with the same original spatial resolution. The mathematical model of the shooting process is provided. It is determined that restoration of spectral radiance of objects based on the shooting data using the proposed method is a mathematically incorrect inverse task. The Greville method, the method of wavelet transformation, the Tikhonov regularisation method, and the Godunov method were considered as methods for its solution. The results of computational modelling of the considered methods are shown and it is found that restoration of spectral radiance of objects based on the shooting data using the considered methods is possible and relative error of restoration is at a fraction of per cent scale. It is determined that the wavelet transformation method is an optimal method of solution of the incorrect spectral radiance restoration task. It is also shown that the proposed method of imaging spectrometry is applicable both when using matrix radiation detectors with increased number of narrow-band filters and when using widely spread standard three-channel matrix RGB detectors of radiation.
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Laszig, R., W. P. Sollmann, and N. Marangos. "The restoration of hearing in neurofibromatosis type 2." Journal of Laryngology & Otology 109, no. 5 (May 1995): 385–89. http://dx.doi.org/10.1017/s0022215100130257.
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AbstractCentral electrical stimulation of the auditory pathway can allow hearing in patients sufferingfrom deafness localized in the auditory nerve. Developments in a multi-channel auditory brainstem implant based on the Nucleus Mini 22 Cochlear implant with transcutaneous signal transmission is discussed. The devices have been implanted in nine European patients suffering from Neurofibromatosis Type 2. Preliminary speech perception results and patient satisfaction are encouraging, and the data presented include some limited open speech recognition.
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Taddia, Yuri, Alberto Pellegrinelli, Corinne Corbau, Giulia Franchi, Lorie W. Staver, John Court Stevenson, and William Nardin. "High-Resolution Monitoring of Tidal Systems Using UAV: A Case Study on Poplar Island, MD (USA)." Remote Sensing 13, no. 7 (April 2, 2021): 1364. http://dx.doi.org/10.3390/rs13071364.
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Tidal processes regulating sediment accretion rates and vegetated platform erosion in tidal systems strongly affect salt marsh evolution. A balance between erosion and deposition in a restored salt marsh is crucial for analyzing restoration strategies to be adopted within a natural context. Marsh morphology is also coupled with tidal mudflats and channel networks and this makes micro-tidal systems crucial for a detailed assessment of restoration interventions. Here, we present a methodological approach for monitoring channel morphodynamics and vegetation variations over a time frame of six years in a low tidal energy salt marsh of the Paul S. Sarbanes Ecosystem Restoration Project at Poplar Island (Maryland, USA). The project is a restoration site where sediment dredged from the shipping channels in the upper Chesapeake Bay is used to restore a tidal marsh habitat in mid-Chesapeake Bay. Aerial surveys with an Unmanned Aerial Vehicle (UAV) have been performed for the high-resolution mapping of a small tidal system. Flight missions were planned to obtain a Ground Sample Distance (GSD) of 2 cm. Structure-from-Motion (SfM) and Multi-View-Stereo (MVS) algorithms have been used to reconstruct the 3D geometry of the site. The mapping of channel morphology and an elevation assessment on the mudflat were performed using orthomosaics, Digital Terrain Models (DTMs) and GNSS survey. The results highlight that the workflow adopted in this pilot work is suitable to assess the geomorphological evolution over time in a micro-tidal system. However, issues were encountered for salt marsh due to the presence of dense vegetation. The UAV-based photogrammetry approach with GNSS RTK ground surveys can hence be replicated in similar sites all over the world to evaluate restoration interventions and to develop new strategies for a better management of existing shorelines.
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Hu Haoran, 胡皓然, 刘辉 Liu Hui, and 黄欢 Huang Huan. "Blind Restoration of Multi-Channel Images Based on Total Variation and Dark Pixels." Laser & Optoelectronics Progress 57, no. 24 (2020): 241016. http://dx.doi.org/10.3788/lop57.241016.
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Monaco, Simone, Salvatore Greco, Alessandro Farasin, Luca Colomba, Daniele Apiletti, Paolo Garza, Tania Cerquitelli, and Elena Baralis. "Attention to Fires: Multi-Channel Deep Learning Models for Wildfire Severity Prediction." Applied Sciences 11, no. 22 (November 22, 2021): 11060. http://dx.doi.org/10.3390/app112211060.
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Wildfires are one of the natural hazards that the European Union is actively monitoring through the Copernicus EMS Earth observation program which continuously releases public information related to such catastrophic events. Such occurrences are the cause of both short- and long-term damages. Thus, to limit their impact and plan the restoration process, a rapid intervention by authorities is needed, which can be enhanced by the use of satellite imagery and automatic burned area delineation methodologies, accelerating the response and the decision-making processes. In this context, we analyze the burned area severity estimation problem by exploiting a state-of-the-art deep learning framework. Experimental results compare different model architectures and loss functions on a very large real-world Sentinel2 satellite dataset. Furthermore, a novel multi-channel attention-based analysis is presented to uncover the prediction behaviour and provide model interpretability. A perturbation mechanism is applied to an attention-based DS-UNet to evaluate the contribution of different domain-driven groups of channels to the severity estimation problem.
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Li, Huihui, Lun Yu, Liang Zhang, and Ning Yang. "Dark Channel Constraint and Alternated Direction Multiplier Optimization of Turbulence Degraded Image Blind Restoration." Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University 36, no. 1 (February 2018): 103–9. http://dx.doi.org/10.1051/jnwpu/20183610103.
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In order to improve the effect of turbulence degraded image restoration, aiming at the problem that the fuzzy solution is easy to be obtained by using the prior information constraint of gradient distribution under the framework of maximum a posteriori probability of blind restoration algorithm, this paper proposes a dark channel constraint and alternated direction multiplier optimization of turbulence degraded image blind restoration method.First, based on the idea of multi-scale, a dark channel prior constraint is imposed on the image and non-negative constraints and energy constraints are imposed on the point spread function at each level.Then, the kernel and image of the current scale are estimated by alternating iterations of coordinate descent method. When the maximum scale is reached, the final estimated blur kernel is obtained.Last, combined with the total variational model, the image details are quickly restored using the alternate direction optimization method. The experimental results show that the prior information constraint used in the proposed algorithm is advantageous to obtain a clear solution, and can converge to the global optimal solution in the total variational model, which can effectively suppress the artifacts produced in the image restoration process and recover a better target image detail.
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Fatima, Bouasria. "The Channel Shortening comparison between OFDM & MC-CDMA System over an ADSL Channel using a Water-filling." International Journal of Electrical and Computer Engineering (IJECE) 9, no. 5 (October 1, 2019): 3695. http://dx.doi.org/10.11591/ijece.v9i5.pp3695-3700.
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<p>In this paper our objective focuses on the development of digital transmission techniques in order to solve the problem of Inter-Symbol Interference (ISI) due to multiple paths and the improvement of Multi-Carrier Code Division Multiple Access (MC-CDMA) system performance. The both algorithm: MERRY algorithm (Multicarrier Equalization by Restoration of Redundancy) called TEQ (Time domain EQualizer) and the power allocation method to allocate appropriate power to each user (Water-filling technique (WF)) [1] is used. Finally, the numerical results show that combining Water Filling with TEQ technique allows to reduce the ISI for MC-CDMA systems.</p>
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Popovic, Dejan, Mirjana Popovic, and Strahinja Dosen. "Neural prostheses for walking restoration." Journal of Automatic Control 18, no. 2 (2008): 63–71. http://dx.doi.org/10.2298/jac0802063p.
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We review the state of the art of multi-channel electrical stimulation (ES) systems with surface electrodes for assistance in the standing and walking of paraplegics and hemiplegics. For the group of complete paraplegics, walking achieved with available ES systems is below their expectations, especially since these systems cannot compete with mobility provided to them by a wheelchair. However, standing and walking with ES systems are beneficial because they contribute to the improvement of physiological functions. For individuals who can stand with some arm support (e.g., paraplegics with incomplete injury and hemiplegics), the current ES systems are an effective augmentation of walking. We suggest that an ES system for walking of incomplete paraplegics and hemiplegics will be better accepted if the stimulation is regulated by a rule-based control, that is, a preprogrammed, sensor-triggered activation of several muscles resulting in normal walking. We present a method to obtain muscle activity profiles from simulation of a customized model of the patient that can be used for the synthesis of rules for control.
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Sudhakara, M., and M. Janaki Meena. "Multi-scale fusion for underwater image enhancement using multi-layer perceptron." IAES International Journal of Artificial Intelligence (IJ-AI) 10, no. 2 (June 1, 2021): 389. http://dx.doi.org/10.11591/ijai.v10.i2.pp389-397.
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<span id="docs-internal-guid-54b35aa6-7fff-0992-ed4c-aca4d05cfcfa"><span>Underwater image enhancement (UIE) is an imperative computer vision activity with many applications and different strategies proposed in recent years. Underwater images are firmly low in quality by a mixture of noise, wavelength dependency, and light attenuation. This paper depicts an effective strategy to improve the quality of degraded underwater images. Existing methods for dehazing in the literature considering dark channel prior utilize two separate phases for evaluating the transmission map (i.e., transmission estimation and transmission refinement). Accurate restoration is not possible with these methods and takes more computational time. A proposed three-step method is an imaging approach that does not need particular hardware or underwater conditions. First, we utilize the multi-layer perceptron (MLP) to comprehensively evaluate transmission maps by base channel, followed by contrast enhancement. Furthermore, a gamma-adjusted version of the MLP recovered image is derived. Finally, the multi-scale fusion method was applied to two attained images. The standardized weight is computed for the two images with three different weights in the fusion process. The quantitative results show that significantly our approach gives the better result with the difference of 0.536, 2.185, and 1.272 for PCQI, UCIQE, and UIQM metrics, respectively, on a single underwater image benchmark dataset. The qualitative results also give better results compared with the state-of-the-art techniques.</span></span>
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Arnaud-Fassetta, Gilles, Gabriel Melun, Paul Passy, Guillaume Brousse, and Olivier Theureaux. "How to Quantify the Dynamics of Single (Straight or Sinuous) and Multiple (Anabranching) Channels from Imagery for River Restoration." Applied Sciences 11, no. 17 (August 31, 2021): 8075. http://dx.doi.org/10.3390/app11178075.
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Since the 2000s, European rivers have undergone restoration works to give them back a little more ‘freedom space’ and consolidate the hydro-sedimentary continuum and biological continuity as required by the Water Framework Directive (WFD). In high-energy rivers, suppression of lateral constraints (embankment removal) leads to geomorphological readjustments in the modification of both the active-channel length and active-channel width. The article provides a new methodological development to overcome the shortcomings of traditional methods (based on diachronic cross-section analysis) unable to simultaneously take into account these geometric adjustments after active-channel restoration. It allows us to follow and precisely quantify the geomorphological changes of the active channel faced to the stakes (i.e., structures or urbanized, recreation or agricultural areas) in the floodplain. The methodology proposes three new indicators (distance from active channel to stakes or floodplain margins as indicator 1; distance from stakes to active channel as indicator 2; diachronic distance as indicator 3) and a metric analysis grid in the 2D Euclidean space. It is applied to the Clamoux River (order 4, Strahler; bankfull, specific stream power: 280 W/m2) in the Aude watershed (Mediterranean France). The paper shows the full potential of this methodological protocol to be able to meet managers’ expectations as closely as possible within the framework of the multi-annual active-channel monitoring.
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Diet, Antoine M., Nicolas Ribière-Tharaud, Martine Villegas, and Geneviève Baudoin. "Front-end HPA/antenna for multi-radio." International Journal of Microwave and Wireless Technologies 4, no. 5 (May 1, 2012): 483–93. http://dx.doi.org/10.1017/s1759078712000372.
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This paper focuses on multi-radio front-end transmitter, a function implied by cognitive radio (0.5–6 GHz). S and C bands standards (wireless local and metropolitan area networks) present a challenge, due to the signal modulation schemes (orthogonal frequency division multiplex (OFDM)/WCDMA, wideband code division multiple access) dynamic (tens of dBs), driving us to a mandatory transmitter linearization. The idea is to provide frequency, flexibility, and average power control of a multi-radio high-efficiency front end for such signals (polar/envelope elimination and restoration (EER) structure). The study implies antennas design and average power control demonstration. Based on a switched mode power amplifier (PA), a discrete detuning is possible to adapt the PA at both “WiMAX” and “Wifi5” frequencies. This architecture amplifies signals with amplitude information. This is coded here by the ΣΔ/PWM (pulse width modulation) technique, to present a constant envelope signal. The amplitude information is restored by a pass-band radio frequency (RF) filter. The antenna can be designed with a notch, to reduce the filtering constraints (selectivity and standards coexistences) and to help in the restoration of amplitude information. Average power control is illustrated by voltage supply variation and results are a possible dynamic of 9.5 dB. To complete the analysis, the simulation of the propagation channel, including antennas, with CST (free space, line of sight) is imported under AGILENT-ADS.
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Lee, Yooho, Dongsan Jun, Byung-Gyu Kim, and Hunjoo Lee. "Enhanced Single Image Super Resolution Method Using Lightweight Multi-Scale Channel Dense Network." Sensors 21, no. 10 (May 12, 2021): 3351. http://dx.doi.org/10.3390/s21103351.
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Super resolution (SR) enables to generate a high-resolution (HR) image from one or more low-resolution (LR) images. Since a variety of CNN models have been recently studied in the areas of computer vision, these approaches have been combined with SR in order to provide higher image restoration. In this paper, we propose a lightweight CNN-based SR method, named multi-scale channel dense network (MCDN). In order to design the proposed network, we extracted the training images from the DIVerse 2K (DIV2K) dataset and investigated the trade-off between the SR accuracy and the network complexity. The experimental results show that the proposed method can significantly reduce the network complexity, such as the number of network parameters and total memory capacity, while maintaining slightly better or similar perceptual quality compared to the previous methods.
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Nan, Tian, and Wengeng Cao. "Effect of Ecological Water Supplement on Groundwater Restoration in the Yongding River Based on Multi-Model Linkage." Water 15, no. 2 (January 16, 2023): 374. http://dx.doi.org/10.3390/w15020374.
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Evaluating the effect of ecological water supplement on groundwater restoration quantitatively could produce positive contributions to both water cycle theory and surface–groundwater conjunctive management. Therefore, in this paper, a groundwater flow numerical model has been established after calculating the river section seepage rate using a fuzzy mathematical method in the Yongding River channel. The simulated results show that the model could accurately reflect the real groundwater dynamic features. Then, a data-driven random forest(RF) model has been established to quantitatively evaluate the contributions of the factors which influence the groundwater level variation. The Nash-Sutcliffe efficiency coefficient(NSE) of the RF model is 0.93. It shows excellent ability to identify the rising zone of groundwater level. The study shows that the infiltration capacity is strong in the upstream area of the Yongding River, and the seepage rate is over 0.7. The lowest seepage rate is 0.19 at the downstream end, while the seepage rate in the middle area is basically between 0.4 and 0.7. From 2018 to 2019, the ecological water supplement of the Yongding River has played a significant role in raising the groundwater level along the river channel. Additionally, its contribution analyzed by the RF model to the change of groundwater level is 25%. Groundwater exploitation is the most important variable affecting the groundwater level variation. The impact depth of groundwater level fluctuation reaches about 10 m. The impact range where the groundwater level average uplifts 1.86 m is 502.13 km2. The influence direction gradually changes from around the ecological water supplement section to along the Yongding River channel. The groundwater level variation along the tangential direction of the Yongding River is slowing down. The groundwater level would entirely uplift with 170 × 106 m3/year ecological water supplement of the Yongding River and 35.77 × 106 m3/year groundwater mining reduction in the downstream area until 2035.
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Clunes, Lucy A., Naia McMillan-Castanares, Neil Mehta, Afia Mesadieu, Jorge Rodriguez, Mary Maj, and Mark T. Clunes. "Epithelial vectorial ion transport in cystic fibrosis: Dysfunction, measurement, and pharmacotherapy to target the primary deficit." SAGE Open Medicine 8 (January 2020): 205031212093380. http://dx.doi.org/10.1177/2050312120933807.
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Cystic fibrosis patients display multi-organ system dysfunction (e.g. pancreas, gastrointestinal tract, and lung) with pathogenesis linked to a failure of Cl− secretion from the epithelial surfaces of these organs. If unmanaged, organ dysfunction starts early and patients experience chronic respiratory infection with reduced lung function and a failure to thrive due to gastrointestinal malabsorption. Early mortality is typically caused by respiratory failure. In the past 40 years of newborn screening and improved disease management have driven the median survival up from the mid-teens to 43–53, with most of that improvement coming from earlier and more aggressive management of the symptoms. In the last decade, promising pharmacotherapies have been developed for the correction of the underlying epithelial dysfunction, namely, Cl− secretion. A new generation of systemic drugs target the mutated Cl− channels in cystic fibrosis patients and allow trafficking of the immature mutated protein to the cell membrane (correctors), restore function to the channel once in situ (potentiators), or increase protein levels in the cells (amplifiers). Restoration of channel function prior to symptom development has the potential to significantly change the trajectory of disease progression and their evidence suggests that a modest restoration of Cl− secretion may delay disease progression by decades. In this article, we review epithelial vectorial ion and fluid transport, its quantification and measurement as a marker for cystic fibrosis ion transport dysfunction, and highlight some of the recent therapies targeted at the dysfunctional ion transport of cystic fibrosis.
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Zhou-xiang Jin, Zhou-xiang Jin, and Hao Qin Zhou-xiang Jin. "Generative Adversarial Network Based on Multi-feature Fusion Strategy for Motion Image Deblurring." 電腦學刊 33, no. 1 (February 2022): 031–41. http://dx.doi.org/10.53106/199115992022023301004.
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<p>Deblurring of motion images is a part of the field of image restoration. The deblurring of motion images is not only difficult to estimate the motion parameters, but also contains complex factors such as noise, which makes the deblurring algorithm more difficult. Image deblurring can be divided into two categories: one is the non-blind image deblurring with known fuzzy kernel, and the other is the blind image deblurring with unknown fuzzy kernel. The traditional motion image deblurring networks ignore the non-uniformity of motion blurred images and cannot effectively recover the high frequency details and remove artifacts. In this paper, we propose a new generative adversarial network based on multi-feature fusion strategy for motion image deblurring. An adaptive residual module composed of deformation convolution module and channel attention module is constructed in the generative network. Where, the deformation convolution module learns the shape variables of motion blurred image features, and can dynamically adjust the shape and size of the convolution kernel according to the deformation information of the image, thus improving the ability of the network to adapt to image deformation. The channel attention module adjusts the extracted deformation features to obtain more high-frequency features and enhance the texture details of the restored image. Experimental results on public available GOPRO dataset show that the proposed algorithm improves the peak signal-to-noise ratio (PSNR) and is able to reconstruct high quality images with rich texture details compared to other motion image deblurring methods.</p> <p> </p>
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Chen, Bingyu, Min Xia, and Junqing Huang. "MFANet: A Multi-Level Feature Aggregation Network for Semantic Segmentation of Land Cover." Remote Sensing 13, no. 4 (February 17, 2021): 731. http://dx.doi.org/10.3390/rs13040731.
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Detailed information regarding land utilization/cover is a valuable resource in various fields. In recent years, remote sensing images, especially aerial images, have become higher in resolution and larger span in time and space, and the phenomenon that the objects in an identical category may yield a different spectrum would lead to the fact that relying on spectral features only is often insufficient to accurately segment the target objects. In convolutional neural networks, down-sampling operations are usually used to extract abstract semantic features, which leads to loss of details and fuzzy edges. To solve these problems, the paper proposes a Multi-level Feature Aggregation Network (MFANet), which is improved in two aspects: deep feature extraction and up-sampling feature fusion. Firstly, the proposed Channel Feature Compression module extracts the deep features and filters the redundant channel information from the backbone to optimize the learned context. Secondly, the proposed Multi-level Feature Aggregation Upsample module nestedly uses the idea that high-level features provide guidance information for low-level features, which is of great significance for positioning the restoration of high-resolution remote sensing images. Finally, the proposed Channel Ladder Refinement module is used to refine the restored high-resolution feature maps. Experimental results show that the proposed method achieves state-of-the-art performance 86.45% mean IOU on LandCover dataset.
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Liu, Changhong, Hongyin Li, Zhongwei Liang, Yongjun Zhang, Yier Yan, Ray Y. Zhong, and Shaohu Peng. "A Novel Deep-Learning-Based Enhanced Texture Transformer Network for Reference Image Super-Resolution." Electronics 11, no. 19 (September 24, 2022): 3038. http://dx.doi.org/10.3390/electronics11193038.
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The study explored a deep learning image super-resolution approach which is commonly used in face recognition, video perception and other fields. These generative adversarial networks usually have high-frequency texture details. The relevant textures of high-resolution images could be transferred as reference images to low-resolution images. The latest existing methods use transformer ideas to transfer related textures to low-resolution images, but there are still some problems with channel learning and detailed textures. Therefore, the study proposed an enhanced texture transformer network (ETTN) to improve the channel learning ability and details of the texture. It could learn the corresponding structural information of high-resolution texture images and convert it into low-resolution texture images. Through this, finding the feature map can change the exact feature of images and improve the learning ability between channels. We then used multi-scale feature integration (MSFI) to further enhance the effect of fusion and achieved different degrees of texture restoration. The experimental results show that the model has a good resolution enhancement effect on texture transformers. In different datasets, the peak signal to noise ratio (PSNR) and structural similarity (SSIM) were improved by 0.1–0.5 dB and 0.02, respectively.
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Kim, Jonghyun, Kyeonghoon Jeong, and Moon Gi Kang. "Crosstalk Correction for Color Filter Array Image Sensors Based on Lp-Regularized Multi-Channel Deconvolution." Sensors 22, no. 11 (June 4, 2022): 4285. http://dx.doi.org/10.3390/s22114285.
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In this paper, we propose a crosstalk correction method for color filter array (CFA) image sensors based on Lp-regularized multi-channel deconvolution. Most imaging systems with CFA exhibit a crosstalk phenomenon caused by the physical limitations of the image sensor. In general, this phenomenon produces both color degradation and spatial degradation, which are respectively called desaturation and blurring. To improve the color fidelity and the spatial resolution in crosstalk correction, the feasible solution of the ill-posed problem is regularized by image priors. First, the crosstalk problem with complex spatial and spectral degradation is formulated as a multi-channel degradation model. An objective function with a hyper-Laplacian prior is then designed for crosstalk correction. This approach enables the simultaneous improvement of the color fidelity and the sharpness restoration of the details without noise amplification. Furthermore, an efficient solver minimizes the objective function for crosstalk correction consisting of Lp regularization terms. The proposed method was verified on synthetic datasets according to various crosstalk and noise levels. Experimental results demonstrated that the proposed method outperforms the conventional methods in terms of the color peak signal-to-noise ratio and structural similarity index measure.
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Alfonso-Torreño, Alberto, Álvaro Gómez-Gutiérrez, and Susanne Schnabel. "Dynamics of Erosion and Deposition in a Partially Restored Valley-Bottom Gully." Land 10, no. 1 (January 13, 2021): 62. http://dx.doi.org/10.3390/land10010062.
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Gullies are sources and reservoirs of sediments and perform as efficient transfers of runoff and sediments. In recent years, several techniques and technologies emerged to facilitate monitoring of gully dynamics at unprecedented spatial and temporal resolutions. Here we present a detailed study of a valley-bottom gully in a Mediterranean rangeland with a savannah-like vegetation cover that was partially restored in 2017. Restoration activities included check dams (gabion weirs and fascines) and livestock exclosure by fencing. The specific objectives of this work were: (1) to analyze the effectiveness of the restoration activities, (2) to study erosion and deposition dynamics before and after the restoration activities using high-resolution digital elevation models (DEMs), (3) to examine the role of micro-morphology on the observed topographic changes, and (4) to compare the current and recent channel dynamics with previous studies conducted in the same study area through different methods and spatio-temporal scales, quantifying medium-term changes. Topographic changes were estimated using multi-temporal, high-resolution DEMs produced using structure-from-motion (SfM) photogrammetry and aerial images acquired by a fixed-wing unmanned aerial vehicle (UAV). The performance of the restoration activities was satisfactory to control gully erosion. Check dams were effective favoring sediment deposition and reducing lateral bank erosion. Livestock exclosure promoted the stabilization of bank headcuts. The implemented restoration measures increased notably sediment deposition.
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Poff, N. LeRoy, and Alexander D. Huryn. "Multi-scale determinants of secondary production in Atlantic salmon (Salmo salar) streams." Canadian Journal of Fisheries and Aquatic Sciences 55, S1 (January 1, 1998): 201–17. http://dx.doi.org/10.1139/d98-013.
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Understanding variation in the freshwater production of Atlantic salmon across its range is a critical aspect of the species' conservation, restoration, and management. We focus on how environmental factors operate at four hierarchical scales (region, watershed, reach, local habitat) to influence the production and survivorship of juvenile salmon and the production of their invertebrate food base. Using published, quantitative information about invertebrate production in small, cold streams characteristic of Altantic salmon nursery streams, we estimate expected maximum salmon production will be ca. 9 (range 6-22)g wet mass · m-2 · year -1, which compares favorably with reported literature values of < 1 to 17 g · m-2. We highlight some empirically based, shortcut approaches to estimating invertebrate production that may be particularly useful for evaluating salmonid production across a range of scales. We also consider how availability of invertebrate prey may influence salmon production. As a synthesis, we integrate existing information into a multi-scale framework by making qualitative predictions (hypotheses) about expected patterns of invertebrate and salmon production at different habitat scales. We then develop quantitative, heuristic scenarios that predict (hypothesize) how salmon and invertebrate production will change in response to selected physicochemical and non-trophic habitat limitations operating at the watershed (geology, land use) and reach (channel form, canopy) scales. Predicted values, which fall within the range of observed values for Atlantic salmon streams, demonstrate that a multi-scale habitat perspective can provide important insights into local to regional variation in the production of Atlantic salmon across its range and thus contribute to Atlantic salmon conservation, restoration, and management.
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Huang, Kuo-Yuan, Chih-Hsiung Chang, Young-Fo Chang, Jia-Wei Liu, and Jer-Wei Chang. "The Feasibility of Shadowed Image Restoration Using the Synthetic Aperture Focusing Technique." Applied Sciences 12, no. 18 (September 16, 2022): 9297. http://dx.doi.org/10.3390/app12189297.
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The phenomenon of acoustic shadowing on ultrasonography is characterized by an echo signal void behind structures that strongly absorb or reflect ultrasonic energy. In medical ultrasonography, once the ultrasound energy is shielded, acoustic shadowing makes it difficult to create an image, leading to misinterpretations and obscure diagnoses. Hence, instead of dealing with the defocused problem encountered in an ultrasound scan (US), this current research focuses on revealing the existence of an acoustically shadowed target (or a potential lesion) using a well-known restoration algorithm, i.e., the synthetic aperture focusing technique (SAFT). To demonstrate the effects of an acoustic shadow on an ultrasound scan (US), a forward model study is carried out. In laboratory manipulations, a purposely designed physical model is created and then scanned using B-mode and pitch/catch arrangements to carry out shadowed and shadow-free scans in a water tank. Thereafter, making use of a delay-and-sum (DAS) operation, the echo signals are processed by the synthetic aperture focusing technique (SAFT) to perform image restoration. The results of the restoration process show that the SAFT algorithm performs well with respect to directional shadowing. Once the target or lesion is positioned in a total anechoic zone, or even in a multi-channel scan, it will fail.
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Максимов, А. И. "EACH FRAME POINT RESTORATION ERROR BASED SUPER-RESOLUTION METHOD." Южно-Сибирский научный вестник, no. 4(38) (August 31, 2021): 30–38. http://dx.doi.org/10.25699/sssb.2021.38.4.011.
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В работе предложен метод повышения пространственного разрешения по серии кадров низкого разрешения, использующий для формирования результирующего изображения значения погрешностей восстановления в точке каждого кадра. Метод объединяет в себе результаты многолетних исследований автора в области повышения качества изображений и видеозаписей. Предложенный метод разрабатывался для решения прикладных задач криминалистической экспертизы видеозаписей и предназначен для повышения визуального качества плоского локального объекта, находящегося близко к центру кадра. Метод состоит из трех этапов. Первый этап - процедура сверхразрешающего восстановления в каждом кадре с учетом непрерывно-дискретной модели наблюдения сигнала с сохранением сведений об ошибке такого восстановления в дополнительный канал обработки изображения. Второй – геометрическое согласование восстановленных кадров с применением геометрического преобразования к дополнительному каналу обработки. Третий – взвешенное оптимальное по критерию минимизации среднеквадратической ошибки комплексирование кадров. Преимуществами предлагаемого метода являются оценка погрешности восстанавливаемого изображения в каждой точке, а также учет искажений изображений в непрерывной области. В работе проведено экспериментальное исследование ошибки восстановления предлагаемого метода, полученные результаты сравнивались со случаем, не использующим авторские находки предлагаемого метода, - усредняющим комплексированием линейно интерполированных кадров. Линейная интерполяция была взята, поскольку она также вписывается в фильтровую модель восстановления изображения на первом этапе работы метода. Полученные результаты демонстрируют превосходство предлагаемого метода. In this paper, a method for multi-frame superresolution is proposed. It exploits the values of the recovery errors at the point of each frame to form the resulting high-resolution image. The method combines the results of many years of author's research in the field of image and video processing. The proposed method aims to apply to forensic tasks of video analysis. The method improves the visual quality of a flat local object located close to the center of the frame. The method consists of three stages. The first stage is the procedure of optimal super-resolution recovery of each frame with the use of the continuous-discrete observation model. During this stage, the recovery errors are stored in an additional image channel. The second stage is the frames registration. A geometric transformation is also applied to the additional channel during this stage. The final stage is the weighted optimal fusing. The advantages of the proposed method are the estimation of the error of the restored image at each point and taking into account the image degradations in the continuous domain. Experimental research of the reconstruction error of the method was carried out. The results were compared with the case that does not use the novel features of the proposed method - averaging fusing of linear interpolated frames. Linear interpolation was chosen as it also fits into the filtering model of image recovery of the method's first stage. The obtained results show that the proposed method outperforms the other one.
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Arnaud, Fanny, Lalandy Sehen Chanu, Jules Grillot, Jérémie Riquier, Hervé Piégay, Dad Roux-Michollet, Georges Carrel, and Jean-Michel Olivier. "Historical cartographic and topo-bathymetric database on the French Rhône River (17th–20th century)." Earth System Science Data 13, no. 5 (May 10, 2021): 1939–55. http://dx.doi.org/10.5194/essd-13-1939-2021.
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Abstract. Space and time analyses of channel changes, especially within large rivers subject to high levels of human impact, are critical to address multiple questions about rivers in the Anthropocene era. The reconstruction of long-term (> 150 year) evolutionary trajectories permits an understanding of how natural and anthropogenic factors impact hydromorphological and ecological processes in rivers, helps with the design of sustainable management and restoration options, and may also help in the assessment of future changes. However, the reconstruction of channel changes can be challenging: historical data are often scattered across many archives, and the quantity and accuracy of information generally decreases as one goes back in time. This data article provides a historical database of 350 cartographic and topo-bathymetric resources on the French Rhône River (530 km in length) compiled from the 17th to mid-20th century, with a temporal focus prior to extensive river training (1860s). The data were collected in 14 national, regional, and departmental archive services. A table describes the properties of each archived data item and its associated iconographic files. Some of the historical maps are available in a georeferenced format. A GIS layer enables one-click identification of all archive data available for a given reach of the French Rhône River. This database provides substantial new material for deeper analyses of channel changes over a longer time period and at a finer time step compared with previously available data. The database has several potential applications in geomorphology, retrospective hydraulic modelling, historical ecology, and river restoration, as well as permitting comparisons with other multi-impacted rivers worldwide. The dataset is available at https://doi.org/10.1594/PANGAEA.922437 (Arnaud et al., 2020a). Iconographic extracts of the 350 archived items are available at http://photo.driihm.fr/index.php/category/52 (last access: 2 May 2021).
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Tuchkovenko, Yu S., D. V. Kushnir, and N. S. Loboda. "Estimation of the influence of water exchange with the sea conditions on the water level and salinity variability in the Tyligulskyi Liman lagoon." Ukrainian hydrometeorological journal, no. 16 (October 29, 2017): 232–41. http://dx.doi.org/10.31481/uhmj.16.2015.30.
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The potentialities of averting a further salinization of the Tyligulskyi Liman lagoon were identified on the basis of the results of the hydrodynamic modelling, using the numerical model Delft3D-FLOW. The means to prevent the salinization in the lagoon include a reconstruction of the “lagoon-sea” interconnecting channel and the changing of its operational schedule, as well as the increasing of the river inflow considering the climatic conditions of the first half of the XXI century. The results of the verification of the hydrodynamic model are given. It is shown that for stabilizing water levels and reducing the rate of the water salinity in the lagoon the most effective option is the year-round operation of the deepened “lagoon-sea” connecting channel. This will be facilitated by a multi-directional exchange of water through the channel caused by wind-induced water level oscillations in the lagoon and in the sea. However, while maintaining the current level of the water management activity in the catchment area of the lagoon, a long-term trend of increasing water salinity in the lagoon still remains. Only the restoration of natural river discharge into the lagoon could reduce the tendency of growing water salinity to a minimum.
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Hsieh, Tung-Chou, Yan Ding, Keh-Chia Yeh, and Ren-Kai Jhong. "Numerical Investigation of Sediment Flushing and Morphological Changes in Tamsui River Estuary through Monsoons and Typhoons." Water 14, no. 11 (June 2, 2022): 1802. http://dx.doi.org/10.3390/w14111802.
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The removal of reservoir silt and the restoration of existing reservoir capacities through land excavation and hydraulic sediment flushing have become necessary. Hydraulic sediment flushing discharge changes flow and sediment conditions of the downstream river channel. In the Tamsui River estuary in Taiwan, sediment flushing from the Shihmen reservoir upstream has potential impacts on the morphology of the navigation channels and the adjacent coasts. This study employed a validated coastal and estuarine processes model to investigate: (1) the influence of sediment flushing and tidal levels on morphological changes during flood and flushing-discharge operations of the reservoir, and (2) the differences in morphological changes on the estuary between monsoon and typhoon seasons. The prediction of the morphological changes was carried out by simulating hydrodynamic and morphodynamic processes under multi-year synthetic conditions combined by northeast monsoon and three historical typhoon events. The simulation results reveal that during the operation of sediment flushing when the peak discharge of river flood flow reaches the estuary section at ebb tides, more sediment can be transported to the open sea than that at flood tides. Additionally, the nature reserve area on the left bank of the estuary is eroded during monsoon and silted in typhoon seasons.
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Song, Zian, Wenjie Luo, and Qingxuan Shi. "Res-CDD-Net: A Network with Multi-Scale Attention and Optimized Decoding Path for Skin Lesion Segmentation." Electronics 11, no. 17 (August 26, 2022): 2672. http://dx.doi.org/10.3390/electronics11172672.
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Melanoma is a lethal skin cancer. In its diagnosis, skin lesion segmentation plays a critical role. However, skin lesions exhibit a wide range of sizes, shapes, colors, and edges. This makes skin lesion segmentation a challenging task. In this paper, we propose an encoding–decoding network called Res-CDD-Net to address the aforementioned aspects related to skin lesion segmentation. First, we adopt ResNeXt50 pre-trained on the ImageNet dataset as the encoding path. This pre-trained ResNeXt50 can provide rich image features to the whole network to achieve higher segmentation accuracy. Second, a channel and spatial attention block (CSAB), which integrates both channel and spatial attention, and a multi-scale capture block (MSCB) are introduced between the encoding and decoding paths. The CSAB can highlight the lesion area and inhibit irrelevant objects. MSCB can extract multi-scale information to learn lesion areas of different sizes. Third, we upgrade the decoding path. Every 3 × 3 square convolution kernel in the decoding path is replaced by a diverse branch block (DBB), which not only promotes the feature restoration capability, but also improves the performance and robustness of the network. We evaluate the proposed network on three public skin lesion datasets, namely ISIC-2017, ISIC-2016, and PH2. The dice coefficient is 6.90% higher than that of U-Net, whereas the Jaccard index is 10.84% higher than that of U-Net (assessed on the ISIC-2017 dataset). The results show that Res-CDD-Net achieves outstanding performance, higher than the performance of most state-of-the-art networks. Last but not least, the training of the network is fast, and good results can be achieved in early stages of training.
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Wang, Zhaoqiu, Tao Sun, Kun Hu, Yueting Zhang, Xiaqiong Yu, and Ying Li. "A Deep Learning Semantic Segmentation Method for Landslide Scene Based on Transformer Architecture." Sustainability 14, no. 23 (December 6, 2022): 16311. http://dx.doi.org/10.3390/su142316311.
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Semantic segmentation technology based on deep learning has developed rapidly. It is widely used in remote sensing image recognition, but is rarely used in natural disaster scenes, especially in landslide disasters. After a landslide disaster occurs, it is necessary to quickly carry out rescue and ecological restoration work, using satellite data or aerial photography data to quickly analyze the landslide area. However, the precise location and area estimation of the landslide area is still a difficult problem. Therefore, we propose a deep learning semantic segmentation method based on Encoder-Decoder architecture for landslide recognition, called the Separable Channel Attention Network (SCANet). The SCANet consists of a Poolformer encoder and a Separable Channel Attention Feature Pyramid Network (SCA-FPN) decoder. Firstly, the Poolformer can extract global semantic information at different levels with the help of transformer architecture, and it greatly reduces computational complexity of the network by using pooling operations instead of a self-attention mechanism. Secondly, the SCA-FPN we designed can fuse multi-scale semantic information and complete pixel-level prediction of remote sensing images. Without bells and whistles, our proposed SCANet outperformed the mainstream semantic segmentation networks with fewer model parameters on our self-built landslide dataset. The mIoU scores of SCANet are 1.95% higher than ResNet50-Unet, especially.
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Burman, Scott G., Jingya Gao, Gregory B. Pasternack, Nann A. Fangue, Paul Cadrett, Elizabeth Campbell, and Dipak Ghosal. "TempMesh – A Flexible Wireless Sensor Network for Monitoring River Temperatures." ACM Transactions on Sensor Networks 19, no. 1 (December 8, 2022): 1–28. http://dx.doi.org/10.1145/3542697.
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For a Chinook salmon restoration project in the lower Yuba River in California, we designed and deployed a wireless sensor network to monitor river temperatures at micro-habitat scales. The study required that temperatures be measured along a 3 km study reach, across the channel, and into off-channel areas. To capture diel and seasonal fluctuations, sensors were sampled quarter-hourly for the full duration of the six-month juvenile salmon winter residency. This sampling duration required that nodes minimize power-use. We adopted event-based software on MSP430 micro-controllers with 433 MHz radio and minimized the networking duty-cycle. To address link failures, we included network storage. As the network lacked real-time clocks, data were timestamped at the destination. This, coupled with the storage, yielded timestamp inaccuracies, which we re-aligned using a novel algorithm. We collected over six months of temperature data from 35 sensors across seven nodes. Of the packets collected, we identified 21% as being incorrectly timestamped and were able to re-align 41% of these incorrectly timestamped packets. We collected temperature data through major floods, and the network uploaded data until the flood destroyed the sensors. The network met an important need in ecological sampling with ultra-low power (multi-year battery life) and low-throughput.
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Li, Zheng, Wentai Zhang, Yilahong Aikebaier, Tong Dong, Guoping Huang, Tao Qu, and Hexin Zhang. "Sustainable Development of Arid Rangelands and Managing Rainwater in Gullies, Central Asia." Water 12, no. 9 (September 10, 2020): 2533. http://dx.doi.org/10.3390/w12092533.
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Along with the global climate change, gully erosion, flood and drought jointly restrict the sustainable development of arid rangeland in Central Asia. Rainwater harvesting (RWH) system in gully is a flexible practice that alleviate complex environmental problems. In the Kulusitai watershed of Xinjiang, China, our study presented a decision-making system using GIS combined with multi-criteria analysis and a field survey to identify suitability of gully for RWH. The results showed that nearly 40% of rangeland belonged to high runoff potential area, and gullies as the runoff collection channel became the potential site of RWH. The selection of RWH systems depended on catchment environment and gully characteristics. Therefore, based on the unique natural conditions of Xinjiang and successful RWH cases in other regions, we discussed some suitable low-cost RWH techniques to restore degraded grassland and promote community development. Our study will provide some suggestions for ecological restoration and pasture management in arid regions of Central Asia.
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Kellogg, Christina A., Ryan P. Moyer, Mary Jacobsen, and Kimberly Yates. "Identifying mangrove-coral habitats in the Florida Keys." PeerJ 8 (August 24, 2020): e9776. http://dx.doi.org/10.7717/peerj.9776.
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Coral reefs are degrading due to many synergistic stressors. Recently there have been a number of global reports of corals occupying mangrove habitats that provide a supportive environment or refugium for corals, sheltering them by reducing stressors such as oxidative light stress and low pH. This study used satellite imagery and manual ground-truthing surveys to search for mangrove-coral habitats in the Florida Keys National Marine Sanctuary and then collected basic environmental parameters (temperature, salinity, dissolved oxygen, pHNBS, turbidity) at identified sites using a multi-parameter water quality sonde. Two kinds of mangrove-coral habitats were found in both the Upper and Lower Florida Keys: (1) prop-root corals, where coral colonies were growing directly on (and around) mangrove prop roots, and (2) channel corals, where coral colonies were growing in mangrove channels under the shade of the mangrove canopy, at deeper depths and not in as close proximity to the mangroves. Coral species found growing on and directly adjacent to prop roots included Porites porites (multiple morphs, including P. divaricata and P. furcata), Siderastrea radians, and Favia fragum. Channel coral habitats predominantly hosted S. radians and a few S. siderea, although single colonies of Solenastrea bournoni and Stephanocoenia intersepta were observed. Although clear, low-turbidity water was a consistent feature of these mangrove-coral habitats, the specific combination of environmental factors that determine which mangrove habitats are favorable for coral recruitment remains to be defined. Circumstantial evidence suggests additional coral communities existed on mangrove shorelines of oceanside and backcountry islands until destroyed, likely by Hurricane Irma. These mangrove-coral habitats may be climate refugia for corals and could be included in ecosystem management plans and considered for their applications in coral restoration.
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Cukur, Deniz, Senay Horozal, Dae C. Kim, and Hyun C. Han. "Seismic stratigraphy and structural analysis of the northern East China Sea Shelf Basin interpreted from multi-channel seismic reflection data and cross-section restoration." Marine and Petroleum Geology 28, no. 5 (May 2011): 1003–22. http://dx.doi.org/10.1016/j.marpetgeo.2011.01.002.
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Shao, Linhao, Erhu Zhang, and Mei Li. "An Efficient Convolutional Neural Network Model Combined with Attention Mechanism for Inverse Halftoning." Electronics 10, no. 13 (June 30, 2021): 1574. http://dx.doi.org/10.3390/electronics10131574.
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Inverse halftoning acting as a special image restoration problem is an ill-posed problem. Although it has been studied in the last several decades, the existing solutions can’t restore fine details and texture accurately from halftone images. Recently, the attention mechanism has shown its powerful effects in many fields, such as image processing, pattern recognition and computer vision. However, it has not yet been used in inverse halftoning. To better solve the problem of detail restoration of inverse halftoning, this paper proposes a simple yet effective deep learning model combined with the attention mechanism, which can better guide the network to remove noise dot-patterns and restore image details, and improve the network adaptation ability. The whole model is designed in an end-to-end manner, including feature extraction stage and reconstruction stage. In the feature extraction stage, halftone image features are extracted and halftone noises are removed. The reconstruction stage is employed to restore continuous-tone images by fusing the feature information extracted in the first stage and the output of the residual channel attention block. In this stage, the attention block is firstly introduced to the field of inverse halftoning, which can make the network focus on informative features and further enhance the discriminative ability of the network. In addition, a multi-stage loss function is proposed to accelerate the network optimization, which is conducive to better reconstruction of the global image. To demonstrate the generalization performance of the network for different types of halftone images, the experiment results confirm that the network can restore six different types of halftone image well. Furthermore, experimental results show that our method outperforms the state-of-the-art methods, especially in the restoration of details and textures.
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Li, Xiuhe, Jinhe Ran, Hao Zhang, and Shunjun Wei. "MCSNet: A Radio Frequency Interference Suppression Network for Spaceborne SAR Images via Multi-Dimensional Feature Transform." Remote Sensing 14, no. 24 (December 14, 2022): 6337. http://dx.doi.org/10.3390/rs14246337.
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Spaceborne synthetic aperture radar (SAR) is a promising remote sensing technique, as it can produce high-resolution imagery over a wide area of surveillance with all-weather and all-day capabilities. However, the spaceborne SAR sensor may suffer from severe radio frequency interference (RFI) from some similar frequency band signals, resulting in image quality degradation, blind spot, and target loss. To remove these RFI features presented on spaceborne SAR images, we propose a multi-dimensional calibration and suppression network (MCSNet) to exploit the features learning of spaceborne SAR images and RFI. In the scheme, a joint model consisting of the spaceborne SAR image and RFI is established based on the relationship between SAR echo and the scattering matrix. Then, to suppress the RFI presented in images, the main structure of MCSNet is constructed by a multi-dimensional and multi-channel strategy, wherein the feature calibration module (FCM) is designed for global depth feature extraction. In addition, MCSNet performs planned mapping on the feature maps repeatedly under the supervision of the SAR interference image, compensating for the discrepancies caused during the RFI suppression. Finally, a detailed restoration module based on the residual network is conceived to maintain the scattering characteristics of the underlying scene in interfered SAR images. The simulation data and Sentinel-1 data experiments, including different landscapes and different forms of RFI, validate the effectiveness of the proposed method. Both the results demonstrate that MCSNet outperforms the state-of-the-art methods and can greatly suppress the RFI in spaceborne SAR.
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EL-KHAMY, S. E., M. M. HADHOUD, M. I. DESSOUKY, B. M. SALAM, and F. E. ABD EL-SAMIE. "WAVELET FUSION: A TOOL TO BREAK THE LIMITS ON LMMSE IMAGE SUPER-RESOLUTION." International Journal of Wavelets, Multiresolution and Information Processing 04, no. 01 (March 2006): 105–18. http://dx.doi.org/10.1142/s0219691306001129.
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This paper presents a wavelet-based computationally efficient implementation of the Linear Minimum Mean Square Error (LMMSE) algorithm in image super-resolution. The image super-resolution reconstruction problem is well-known to be an ill-posed inverse problem of large dimensions. The LMMSE estimator to be implemented in the image super-resolution reconstruction problem requires an inversion of a very large dimension matrix, which is practically impossible. Our suggested implementation is based on breaking the problem into four consecutive steps, a registration step, a multi-channel LMMSE restoration step, a wavelet-based image fusion step and an LMMSE image interpolation step. The objective of the wavelet fusion step is to integrate the data obtained from each observation into a single image, which is then interpolated to give a high-resolution image. The paper explains the implementation of each step. The proposed implementation has succeeded in obtaining a high-resolution image from multiple degraded observations with a high PSNR. The computation time of the suggested implementation is small when compared to traditional iterative image super-resolution algorithms.
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Wang, Anyi, Zhiyuan Feng, Xuhong Li, and Yong Pan. "Mine Intelligent Receiver: MIMO-OFDM Intelligent Receiver for Mine Information Recovery." Energies 15, no. 18 (September 7, 2022): 6550. http://dx.doi.org/10.3390/en15186550.
Full textAbstract:
With the advancement of an intellectual and numerical society, the coal mining industry has also begun to change to intelligence. As an important aspect of intelligent coal mine construction, coal mine communication has put forward more stringent standards for communication quality. For the complex communication environment in mines, the transmission of communication signals is always damaged by various noises and interferences, resulting in serious distortion of the communication signals received at the receiving end. Therefore, the use of traditional receivers for information recovery has the problem of high bit error rate (BER), which cannot meet the standard of intelligent coal mine construction. Based on this, the aim of this research is to combine convolutional neural networks (CNN) and multi-input multi-output orthogonal frequency division multiplexing (MIMO-OFDM) communication systems to design an intelligent receiver model for complex mine communication systems. At the receiver side, CNNs are used to take the place of all the information processing processes. First, features are extracted from the received IQ signal by the convolutional neural network, and then the original information bit is recovered using a multi-label classifier to finally realize end-to-end information restoration. The experimental results show that the intelligent receiver model designed in this research has more accurate information recovery capability in the complex mine channel environment compared with the traditional receiver. In addition, they also verify that the intelligent receiver can still recover information effectively when the traditional receiver cannot recover information properly in the case of partial loss of received data.
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Dalsasso, Emanuele, Xiangli Yang, Loïc Denis, Florence Tupin, and Wen Yang. "SAR Image Despeckling by Deep Neural Networks: from a Pre-Trained Model to an End-to-End Training Strategy." Remote Sensing 12, no. 16 (August 15, 2020): 2636. http://dx.doi.org/10.3390/rs12162636.
Full textAbstract:
Speckle reduction is a longstanding topic in synthetic aperture radar (SAR) images. Many different schemes have been proposed for the restoration of intensity SAR images. Among the different possible approaches, methods based on convolutional neural networks (CNNs) have recently shown to reach state-of-the-art performance for SAR image restoration. CNN training requires good training data: many pairs of speckle-free/speckle-corrupted images. This is an issue in SAR applications, given the inherent scarcity of speckle-free images. To handle this problem, this paper analyzes different strategies one can adopt, depending on the speckle removal task one wishes to perform and the availability of multitemporal stacks of SAR data. The first strategy applies a CNN model, trained to remove additive white Gaussian noise from natural images, to a recently proposed SAR speckle removal framework: MuLoG (MUlti-channel LOgarithm with Gaussian denoising). No training on SAR images is performed, the network is readily applied to speckle reduction tasks. The second strategy considers a novel approach to construct a reliable dataset of speckle-free SAR images necessary to train a CNN model. Finally, a hybrid approach is also analyzed: the CNN used to remove additive white Gaussian noise is trained on speckle-free SAR images. The proposed methods are compared to other state-of-the-art speckle removal filters, to evaluate the quality of denoising and to discuss the pros and cons of the different strategies. Along with the paper, we make available the weights of the trained network to allow its usage by other researchers.
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Aldalbahi, Adel, Farzad Shahabi, and Mohammed Jasim. "Instantaneous Beam Prediction Scheme against Link Blockage in mmWave Communications." Applied Sciences 11, no. 12 (June 17, 2021): 5601. http://dx.doi.org/10.3390/app11125601.
Full textAbstract:
Millimeter wave (mmWave) bands formulate the standalone (SA) operation mode in the new radio (NR) access technology of 5G systems. These bands rely on beamforming architectures to aggregate antenna array gains that compensate for dynamic channel fluctuations and propagation impairments. However, beamforming results in directional transmission and reception, thus resulting in beam management challenges, foremost initial access, handover, and beam blockage recovery. Here, beam establishment and maintenance must feature ultra-low latencies in the control and data planes to meet network specifications and standardization. Presently, existing schemes rely on arrays redundancy, multi-connectivity, such as dual-beam and carrier aggregation, and out-of-band information. These schemes still suffer from prolonged recovery times and aggregated power consumption levels. Along these lines, this work proposes a fast beam restoration scheme based on deep learning in SA mmWave networks. Once the primary beam is blocked, it predicts alternative beam directions in the next time frame without any reliance on out-of-band information. The scheme adopts long short-term memory (LSTM) due to the robust memory structure, which uses past best beam observations. The scheme achieves near-instantaneous recovery times, i.e., maintaining communications sessions without resetting beam scanning procedures.