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Auteur : Grafiati
Publié le 11 mars 2023

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1

Hamzah, Rostam Affendi, A. F. Kadmin, S. F. A. Gani, K. A. Aziz, T. M. F. T. Wook, N. Mohamood et M. G. Y. Wei. « A study of edge preserving filters in image matching ». Bulletin of Electrical Engineering and Informatics 10, no 1 (1 février 2021) : 111–17. http://dx.doi.org/10.11591/eei.v10i1.1947.

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This article presents a study on edge preserving filters in image matching which comprises a development of stereo matching algorithm using two edge preserving filters. Fundamentally, the framework is reconstructed by several sequential processes. The output of these processes is a disparity map or depth map. The corresponding points between two images require accurate matching to make accurate depth map estimation. Thus, the propose work in this article utilizes sum of squared differences (SSD) with dual edge preserving filters. These filters are used due to edge preserved properties and to increase the accuracy. The median filter (MF) and bilateral filter (BF) will be utilized. The SSD produces preliminary results with low noise and the edge preserving filters reduce noise on the low texture regions with edge preserving properties. Based on the experimental analysis using the standard benchmarking evaluation system from the Middlebury, the disparity map produced is 6.65% for all error pixels. It shows an accurate edge preserved properties on the disparity maps. To make the proposed work more reliable with current available methods, the quantitative measurement has been made to compare with other existing methods and it displays the proposed work in this article perform much better.
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Toet, Alexander. « Alternating guided image filtering ». PeerJ Computer Science 2 (27 juin 2016) : e72. http://dx.doi.org/10.7717/peerj-cs.72.

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Edge preserving filters aim to simplify the representation of images (e.g., by reducing noise or eliminating irrelevant detail) while preserving their most significant edges. These filters are typically nonlinear and locally smooth the image structure while minimizing both blurring and over-sharpening of visually important edges. Here we present the Alternating Guided Filter (AGF) that achieves edge preserving smoothing by combining two recently introduced filters: the Rolling Guided Filter (RGF) and the Smooth and iteratively Restore Filter (SiR). We show that the integration of RGF and SiR in an alternating iterative framework results in a new smoothing operator that preserves significant image edges while effectively eliminating small scale details. The AGF combines the large scale edge and local intensity preserving properties of the RGF with the edge restoring properties of the SiR while eliminating the drawbacks of both previous methods (i.e., edge curvature smoothing by RGF and local intensity reduction and restoration of small scale details near large scale edges by SiR). The AGF is simple to implement and efficient, and produces high-quality results. We demonstrate the effectiveness of AGF on a variety of images, and provide a public code to facilitate future studies.
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Reddy, Kamireddy Rasool, Madhava Rao Ch et Nagi Reddy Kalikiri. « Performance Assessment of Edge Preserving Filters ». International Journal of Information System Modeling and Design 8, no 2 (avril 2017) : 1–29. http://dx.doi.org/10.4018/ijismd.2017040101.

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Denoising is one of the important aspects in image processing applications. Denoising is the process of eliminating the noise from the noisy image. In most cases, noise accumulates at the edges. So that prevention of noise at edges is one of the most prominent problem. There are numerous edge preserving approaches available to reduce the noise at edges in that Gaussian filter, bilateral filter and non-local means filtering are the popular approaches but in these approaches denoised image suffer from blurring. To overcome these problems, in this article a Gaussian/bilateral filtering (G/BF) with a wavelet thresholding approach is proposed for better image denoising. The performance of the proposed work is compared with some edge-preserving filter algorithms such as a bilateral filter and the Non-Local Means Filter, in terms that objectively assess quality. From the simulation results, it is found that the performance of proposed method is superior to the bilateral filter and the Non-Local Means Filter.
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Ince, Ibrahim Furkan, Omer Faruk Ince et Faruk Bulut. « MID Filter : An Orientation-Based Nonlinear Filter For Reducing Multiplicative Noise ». Electronics 8, no 9 (26 août 2019) : 936. http://dx.doi.org/10.3390/electronics8090936.

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In this study, an edge-preserving nonlinear filter is proposed to reduce multiplicative noise by using a filter structure based on mathematical morphology. This method is called the minimum index of dispersion (MID) filter. MID is an improved and extended version of MCV (minimum coefficient of variation) and MLV (mean least variance) filters. Different from these filters, this paper proposes an extra-layer for the value-and-criterion function in which orientation information is employed in addition to the intensity information. Furthermore, the selection function is re-modeled by performing low-pass filtering (mean filtering) to reduce multiplicative noise. MID outputs are benchmarked with the outputs of MCV and MLV filters in terms of structural similarity index (SSIM), peak signal-to-noise ratio (PSNR), mean squared error (MSE), standard deviation, and contrast value metrics. Additionally, F Score, which is a hybrid metric that is the combination of all five of those metrics, is presented in order to evaluate all the filters. Experimental results and extensive benchmarking studies show that the proposed method achieves promising results better than conventional MCV and MLV filters in terms of robustness in both edge preservation and noise removal. Noise filter methods normally cannot give better results in noise removal and edge-preserving at the same time. However, this study proves a great contribution that MID filter produces better results in both noise cleaning and edge preservation.
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Hussein, Ahmed A., et Xiaochun Yang. « Colorization using edge-preserving smoothing filter ». Signal, Image and Video Processing 8, no 8 (4 décembre 2012) : 1681–89. http://dx.doi.org/10.1007/s11760-012-0402-5.

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Hamdan, Suhad A. « A nonlinear edge –preserving smoothing filter for edge detection on color and gray satellite images ». Iraqi Journal of Physics (IJP) 13, no 26 (10 février 2019) : 29–37. http://dx.doi.org/10.30723/ijp.v13i26.280.

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A nonlinear filter for smoothing color and gray imagescorrupted by Gaussian noise is presented in this paper. The proposedfilter designed to reduce the noise in the R,G, and B bands of thecolor images and preserving the edges. This filter applied in order toprepare images for further processing such as edge detection andimage segmentation.The results of computer simulations show that the proposedfilter gave satisfactory results when compared with the results ofconventional filters such as Gaussian low pass filter and median filterby using Cross Correlation Coefficient (ccc) criteria.
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Guarnieri, G., S. Marsi et G. Ramponi. « Fast bilateral filter for edge-preserving smoothing ». Electronics Letters 42, no 7 (2006) : 396. http://dx.doi.org/10.1049/el:20064369.

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Sivakumar, K., Sakthiraam B, Santosh Snehal. V et Yogashivasankarri S. « Comparative analysis of elementary and edge-preserving spatial filters in noise removal – a comprehensive study ». Journal of University of Shanghai for Science and Technology 23, no 06 (22 juin 2021) : 1244–51. http://dx.doi.org/10.51201/jusst/21/06448.

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Preserving the edges and information is one of the main purposes of edge-preserving filters. That is, they’re employed to smooth a picture, and minimize halos, phantoms, and edge blur over the edge. They have a nonlinear relationship between one thing and another. Bilateral filters, anisotropic diffusion filters, directed filters, and trilateral filters are all types of example filters. The filter family may be used in a wide range of image processing tasks, such as denoising, video abstraction, demosaicing, optical flow estimation, stereo matching, tone mapping, style transfer, relighting, and others. The paper gives a clear description of edge-preserving filters, from the heat diffusion equation in ancient times to the present, explaining their numerous applications and detailing their numerous uses. Additionally, mathematical analysis is included, as well as efficient and optimized implementations. The focus is on preserving the boundaries, spikes, and canyons, and the information is given clearly and in detail. Finally, it offers a realistic representation of efficient implementation, as well as a comprehensive research scope for future hardware implementation.
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Sung, Thai Leang, et Hyo Jong Lee. « Depth edge detection using edge-preserving filter and morphological operations ». International Journal of System Assurance Engineering and Management 11, no 4 (5 septembre 2019) : 812–17. http://dx.doi.org/10.1007/s13198-019-00881-y.

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Anagaw, Amsalu Y., et Mauricio D. Sacchi. « Edge-preserving smoothing for simultaneous-source full-waveform inversion model updates in high-contrast velocity models ». GEOPHYSICS 83, no 2 (1 mars 2018) : A33—A37. http://dx.doi.org/10.1190/geo2017-0563.1.

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Full-waveform inversion (FWI) can provide accurate estimates of subsurface model parameters. In spite of its success, the application of FWI in areas with high-velocity contrast remains a challenging problem. Quadratic regularization methods are often adopted to stabilize inverse problems. Unfortunately, edges and sharp discontinuities are not adequately preserved by quadratic regularization techniques. Throughout the iterative FWI method, an edge-preserving filter, however, can gently incorporate sharpness into velocity models. For every point in the velocity model, edge-preserving smoothing assigns the average value of the most uniform window neighboring the point. Edge-preserving smoothing generates piecewise-homogeneous images with enhanced contrast at boundaries. We adopt a simultaneous-source frequency-domain FWI, based on quasi-Newton optimization, in conjunction with an edge-preserving smoothing filter to retrieve high-contrast velocity models. The edge-preserving smoothing filter gradually removes the artifacts created by simultaneous-source encoding. We also have developed a simple model update to prevent disrupting the convergence of the optimization algorithm. Finally, we perform tests to examine our algorithm.
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11

Xian-Hong, Liu, et Chen Zhi-Bin. « Image Fusion Method Based on Multi-scale Directional Fast Guided Filter and Convolutional Sparse Representation ». Recent Advances in Electrical & ; Electronic Engineering (Formerly Recent Patents on Electrical & ; Electronic Engineering) 12, no 3 (10 juin 2019) : 263–69. http://dx.doi.org/10.2174/2352096511666180607101743.

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Background: A multi-scale multidirectional image fusion method is proposed, which introduces the Nonsubsampled Directional Filter Bank (NSDFB) into the multi-scale edge-preserving decomposition based on the fast guided filter. Methods: The proposed method has the advantages of preserving edges and extracting directional information simultaneously. In order to get better-fused sub-bands coefficients, a Convolutional Sparse Representation (CSR) based approximation sub-bands fusion rule is introduced and a Pulse Coupled Neural Network (PCNN) based detail sub-bands fusion strategy with New Sum of Modified Laplacian (NSML) to be the external input is also presented simultaneously. Results: Experimental results have demonstrated the superiority of the proposed method over conventional methods in terms of visual effects and objective evaluations. Conclusion: In this paper, combining fast guided filter and nonsubsampled directional filter bank, a multi-scale directional edge-preserving filter image fusion method is proposed. The proposed method has the features of edge-preserving and extracting directional information.
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12

Iqbal, Nasar, Sadiq Ali, Imran Khan et Byung Lee. « Adaptive Edge Preserving Weighted Mean Filter for Removing Random-Valued Impulse Noise ». Symmetry 11, no 3 (18 mars 2019) : 395. http://dx.doi.org/10.3390/sym11030395.

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This paper proposes an adaptive noise detector and a new weighted mean filter to remove random-valued impulse noise from the images. Unlike other noise detectors, the proposed detector computes a new and adaptive threshold for each pixel. The detection accuracy is further improved by employing edge identification stage to ensure that the edge pixels are not incorrectly detected as noisy pixels. Thus, preserving the edges avoids faulty detection of noise. In the filtering stage, a new weighted mean filter is designed to filter only those pixels which are identified as noisy in the first stage. Different from other filters, the proposed filter divides the pixels into clusters of noisy and clean pixels and thus takes into only clean pixels to find the replacement of the noisy pixel. Simulation results show that the proposed method outperforms state-of-the-art noise detection methods in suppressing random valued impulse noise.
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Christopher, Prayline Rajabai, et Sivanantham Sathasivam. « Quality Assessment of Dual-Parallel Edge Deblocking Filter Architecture for HEVC/H.265 ». Applied Sciences 12, no 24 (16 décembre 2022) : 12952. http://dx.doi.org/10.3390/app122412952.

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Preserving the visual quality is a major constraint for any algorithm in image and video processing applications. AVC and HEVC are the extensively used video coding standards for various video processing applications in recent days. These coding standards use filters to preserve the visual quality of the processed video. To retain the quality of the reconstructed video, AVC uses an in-loop filter, called the deblocking filter, while HEVC uses two in-loop filters, the sampling adaptive offset filter and the deblocking filter. These filters are implemented in hardware by adopting various optimization techniques such as reduction of power utilization, reduction of algorithm complexity, and consuming lesser area. The quality of the reconstructed video should not be impacted by these optimization measures. For the HEVC/H.265 coding standard, a parallel edge deblocking filter architecture is designed, and the effectiveness of the parallel edge filter architecture is evaluated using various quantization values for various resolutions. The quality of the parallel edge filter architecture is on par with the HEVC reference model.
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14

Li, Xiong. « Terracing gravity and magnetic data using edge-preserving smoothing filters ». GEOPHYSICS 81, no 2 (1 mars 2016) : G41—G47. http://dx.doi.org/10.1190/geo2015-0409.1.

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One major purpose of gravity and magnetic transformations is to produce a result that can be related to geology. The terracing operator achieves this purpose by converting gravity and magnetic data into a geologic map-like field wherein homogeneous domains with sharp domain boundaries are defined. Edge-preserving smoothing filters developed in image processing have the same capability. I have applied the Kuwahara, mean of least variance, and symmetric nearest neighbor filters to gravity and magnetic data. Synthetic and field data examples suggest that these edge-preserving smoothing filters produce terraced effects cleaner than the terracing operator, and the mean of least variance filter often produces the cleanest and sharpest result.
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Xie, Zhi-Feng, Rynson W. H. Lau, Yan Gui, Min-Gang Chen et Li-Zhuang Ma. « A gradient-domain-based edge-preserving sharpen filter ». Visual Computer 28, no 12 (19 janvier 2012) : 1195–207. http://dx.doi.org/10.1007/s00371-011-0668-6.

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Fan, Wanshu, Zhixun Su, Hongyan Wang, Nannan Li et Xuan Wang. « Edge-preserving filter with adaptive L0 gradient optimization ». International Journal of Distributed Sensor Networks 15, no 2 (février 2019) : 155014771982694. http://dx.doi.org/10.1177/1550147719826946.

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Maeda, Yoshihiro, Norishige Fukushima et Hiroshi Matsuo. « Effective Implementation of Edge-Preserving Filtering on CPU Microarchitectures ». Applied Sciences 8, no 10 (19 octobre 2018) : 1985. http://dx.doi.org/10.3390/app8101985.

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In this paper, we propose acceleration methods for edge-preserving filtering. The filters natively include denormalized numbers, which are defined in IEEE Standard 754. The processing of the denormalized numbers has a higher computational cost than normal numbers; thus, the computational performance of edge-preserving filtering is severely diminished. We propose approaches to prevent the occurrence of the denormalized numbers for acceleration. Moreover, we verify an effective vectorization of the edge-preserving filtering based on changes in microarchitectures of central processing units by carefully treating kernel weights. The experimental results show that the proposed methods are up to five-times faster than the straightforward implementation of bilateral filtering and non-local means filtering, while the filters maintain the high accuracy. In addition, we showed effective vectorization for each central processing unit microarchitecture. The implementation of the bilateral filter is up to 14-times faster than that of OpenCV. The proposed methods and the vectorization are practical for real-time tasks such as image editing.
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Yuan, Quan, Zhenyun Peng, Zhencheng Chen, Yanke Guo, Bin Yang et Xiangyan Zeng. « Edge-Preserving Median Filter and Weighted Coding with Sparse Nonlocal Regularization for Low-Dose CT Image Denoising Algorithm ». Journal of Healthcare Engineering 2021 (26 juillet 2021) : 1–7. http://dx.doi.org/10.1155/2021/6095676.

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The impulse noise in CT image was removed based on edge-preserving median filter algorithm. The sparse nonlocal regularization algorithm weighted coding was used to remove the impulse noise and Gaussian noise in the mixed noise, and the peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM) were calculated to evaluate the quality of the denoised CT image. It was found that in nine different proportions of Gaussian noise and salt-and-pepper noise in Shepp-Logan image and CT image processing, the PSNR and SSIM values of the proposed denoising algorithm based on edge-preserving median filter (EP median filter) and weighted encoding with sparse nonlocal regularization (WESNR) were significantly higher than those of using EP median filter and WESNR alone. It was shown that the weighted coding algorithm based on edge-preserving median filtering and sparse nonlocal regularization had potential application value in low-dose CT image denoising.
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ABIKO, Ryo, et Masaaki IKEHARA. « Fast Edge Preserving 2D Smoothing Filter Using Indicator Function ». IEICE Transactions on Information and Systems E102.D, no 10 (1 octobre 2019) : 2025–32. http://dx.doi.org/10.1587/transinf.2018edp7437.

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Mozerov, Mikhail G., et Joost van de Weijer. « Improved Recursive Geodesic Distance Computation for Edge Preserving Filter ». IEEE Transactions on Image Processing 26, no 8 (août 2017) : 3696–706. http://dx.doi.org/10.1109/tip.2017.2705427.

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Zhu, Zhu, Julang Jiang et Xiaoguo Zhang. « Edge-preserving regularized filter with visual perception outlier measurement ». International Journal of Computers and Applications 37, no 3-4 (2 octobre 2015) : 120–26. http://dx.doi.org/10.1080/1206212x.2016.1188567.

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OH, Young-Jin, et Hang-Bong Kang. « Edge Preserving using HOG Guide Filter for Image Segmentation ». Journal of Korea Multimedia Society 18, no 10 (30 octobre 2015) : 1164–71. http://dx.doi.org/10.9717/kmms.2015.18.10.1164.

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Lo, Kai-Han, Yu-Chiang Frank Wang et Kai-Lung Hua. « Edge-Preserving Depth Map Upsampling by Joint Trilateral Filter ». IEEE Transactions on Cybernetics 48, no 1 (janvier 2018) : 371–84. http://dx.doi.org/10.1109/tcyb.2016.2637661.

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Vitale, S., G. Ferraioli et V. Pascazio. « EDGE PRESERVING CNN SAR DESPECKLING ALGORITHM ». ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3/W12-2020 (4 novembre 2020) : 97–100. http://dx.doi.org/10.5194/isprs-archives-xlii-3-w12-2020-97-2020.

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Abstract. SAR despeckling is a key tool for Earth Observation. Interpretation of SAR images are impaired by speckle, a multiplicative noise related to interference of backscattering from the illuminated scene towards the sensor. Reducing the noise is a crucial task for the understanding of the scene. Based on the results of our previous solution KL-DNN, in this work we define a new cost function for training a convolutional neural network for despeckling. The aim is to control the edge preservation and to better filter man-made structures and urban areas that are very challenging for KL-DNN. The results show a very good improvement on the not homogeneous areas keeping the good results in the homogeneous ones. Result on both simulated and real data are shown in the paper.
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Zheng, Shijing, Xiaohong Meng et Jun Wang. « An edge-assisted smooth method for potential field data ». Journal of Geophysics and Engineering 18, no 1 (février 2021) : 113–23. http://dx.doi.org/10.1093/jge/gxaa072.

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Abstract Edge detection is one of the most commonly used methods for the interpretation of potential field data, because it can highlight the horizontal inhomogeneous of underground geological bodies (faults, tectonic boundaries, etc.). A variety of edge detection methods have been reported in the literature, most of which are based on the combined transformation results of horizontal and vertical derivatives of the observations. Consequently, these edge detection methods are sensitive to noise. Therefore, noise reduction is desirable ahead of applying edge detection methods. However, the application of conventional filters smears discontinuities in the data to a certain extent, which would inevitably induce unfavourable influence on subsequent edge detection. To solve this problem, a novel edge-preserving smooth method for potential field data is proposed, which is based on the concept of guided filter developed for image processing. The new method substitutes each data point by a combination of a series of coefficients of linear functions. It was tested on synthetic model and real data, and the results showed that it can effectively smooth potential field data while preserving major structural and stratigraphic discontinuities. The obtained data from the new filter contain more obvious features of existing faults, which brings advantageous to further geological interpretations.
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Belyaev, Alexander G., et Pierre-Alain Fayolle. « Two iterative methods for reverse image filtering ». Signal, Image and Video Processing 15, no 7 (8 avril 2021) : 1565–73. http://dx.doi.org/10.1007/s11760-021-01889-3.

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AbstractWe consider the problem of recovering an original image $${\varvec{x}}$$ x from its filtered version $${\varvec{y}}={\varvec{f}}({\varvec{x}})$$ y = f ( x ) , assuming that the internal structure of the filter $${\varvec{f}}(\cdot )$$ f ( · ) is unknown to us (i.e., we can only query the filter as a black-box and, for example, cannot invert it). We present two new iterative methods to attack the problem, analyze, and evaluate them on various smoothing and edge-preserving image filters.
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Dai, Ronghuo, Cheng Yin, Nueraili Zaman et Fanchang Zhang. « Seismic inversion with adaptive edge-preserving smoothing preconditioning on impedance model ». GEOPHYSICS 84, no 1 (1 janvier 2019) : R11—R19. http://dx.doi.org/10.1190/geo2016-0672.1.

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Poststack seismic impedance inversion is an effective approach for reservoir prediction. Due to the sensitivity to noise and the oscillation near the bed boundary, Gaussian distribution constrained seismic inversion is unfavorable to delineate the subtle-reservoir and small-scale geologic features. To overcome this shortcoming, we have developed a new method that incorporates a priori knowledge in the seismic inversion through a preconditioning impedance model using the adaptive edge-preserving smoothing (Ad-EPS) filter. The Ad-EPS filter preconditioned impedance model for a blocky solution makes the formation interfaces and geologic edges more precise and sharper in the inverted impedance results and keeps the inversion procedure robust even if random noise exists in the seismic data. Furthermore, compared with the conventional EPS filter, the Ad-EPS filter is able to resolve thick and thin geologic features through window size scanning, which is used to find the best-fitting window size for each sample to be filtered. The results of numerical examples and real seismic data test indicate that our inversion method can suppress noise to obtain a “blocky” inversion result and preserve small geologic features.
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LIANG, Lingyu, et Lianwen JIN. « A New Face Relighting Method Based on Edge-Preserving Filter ». IEICE Transactions on Information and Systems E96.D, no 12 (2013) : 2904–7. http://dx.doi.org/10.1587/transinf.e96.d.2904.

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Roomi,. « A Particle Swarm Optimization Based Edge Preserving Impulse Noise Filter ». Journal of Computer Science 6, no 9 (1 septembre 2010) : 1014–20. http://dx.doi.org/10.3844/jcssp.2010.1014.1020.

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NEELIMA, MOHINDRU PANKAJ et MOHINDRU POOJA. « Image Edge Preserving Filter with Impulse Noise Detection and Removal ». i-manager's Journal on Digital Signal Processing 4, no 2 (2016) : 24. http://dx.doi.org/10.26634/jdp.4.2.5995.

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Su, Zhuo, Xiaonan Luo, Zhengjie Deng, Yun Liang et Zhen Ji. « Edge-Preserving Texture Suppression Filter Based on Joint Filtering Schemes ». IEEE Transactions on Multimedia 15, no 3 (avril 2013) : 535–48. http://dx.doi.org/10.1109/tmm.2012.2237025.

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Maeda, Junji, Takehiro Harada, Sato Saga et Yukinori Suzuki. « Anisotropic Dynamic-Morphological-Diffusion for Segmentation of Noisy Color Images ». Journal of Advanced Computational Intelligence and Intelligent Informatics 18, no 2 (20 mars 2014) : 204–12. http://dx.doi.org/10.20965/jaciii.2014.p0204.

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In this paper, we propose a modified anisotropic diffusion algorithm using the dynamicmorphological filtering as a new precise edge-preserving smoothing technique for an accurate segmentation of color images with heavy noise. We incorporate a dynamic selection of multiple structuring elements for each pixel in the morphological filter before the anisotropic diffusion in order to improve the ability of edge-preserving smoothing. As a result, noise and unnecessary details of images are effectively smoothed while preserving small image structures before performing a segmentation algorithm. Several simulated examples are presented that demonstrate the effectiveness of the proposed technique.
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Cheng, Sheng-Wei, Yi-Ting Lin et Yan-Tsung Peng. « A Fast Two-Stage Bilateral Filter Using Constant Time O(1) Histogram Generation ». Sensors 22, no 3 (25 janvier 2022) : 926. http://dx.doi.org/10.3390/s22030926.

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Bilateral Filtering (BF) is an effective edge-preserving smoothing technique in image processing. However, an inherent problem of BF for image denoising is that it is challenging to differentiate image noise and details with the range kernel, thus often preserving both noise and edges in denoising. This letter proposes a novel Dual-Histogram BF (DHBF) method that exploits an edge-preserving noise-reduced guidance image to compute the range kernel, removing isolated noisy pixels for better denoising results. Furthermore, we approximate the spatial kernel using mean filtering based on column histogram construction to achieve constant-time filtering regardless of the kernel radius’ size and achieve better smoothing. Experimental results on multiple benchmark datasets for denoising show that the proposed DHBF outperforms other state-of-the-art BF methods.
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Behar, V., et V. Bogdanova. « Pre-Processing of Hyperspectral Images Using Nonlinear Filters ». Information Technologies and Control 11, no 1 (1 mars 2013) : 8–13. http://dx.doi.org/10.2478/itc-2013-0002.

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Abstract In this paper the use of a set of nonlinear edge-preserving filters is proposed as a pre-processing stage with the purpose to improve the quality of hyperspectral images before object detection. The capability of each nonlinear filter to improve images, corrupted by spatially and spectrally correlated Gaussian noise, is evaluated in terms of the average Improvement factor in the Peak Signal to Noise Ratio (IPSNR), estimated at the filter output. The simulation results demonstrate that this pre-processing procedure is efficient only in case the spatial and spectral correlation coefficients of noise do not exceed the value of 0.6
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LIU, Xin, Hong-wei GE et Bing-chun XU. « Edge-preserving filter with similarity noise detection for impulse noise reduction ». Journal of Computer Applications 32, no 3 (2 avril 2013) : 739–41. http://dx.doi.org/10.3724/sp.j.1087.2012.00739.

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Agarwal, Rashi. « Edge Preserving BIT-Plane Adaptive Wiener Filter for Gaussian Noise Restoration ». International Journal of Computer Applications 108, no 12 (18 décembre 2014) : 28–31. http://dx.doi.org/10.5120/18964-0305.

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Treece, Graham. « The Bitonic Filter : Linear Filtering in an Edge-Preserving Morphological Framework ». IEEE Transactions on Image Processing 25, no 11 (novembre 2016) : 5199–211. http://dx.doi.org/10.1109/tip.2016.2605302.

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Soltanian-Zadeh, H., J. P. Windham et A. E. Yagle. « A multidimensional nonlinear edge-preserving filter for magnetic resonance image restoration ». IEEE Transactions on Image Processing 4, no 2 (1995) : 147–61. http://dx.doi.org/10.1109/83.342189.

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Gang Dong et S. T. Acton. « On the Convergence of Bilateral Filter for Edge-Preserving Image Smoothing ». IEEE Signal Processing Letters 14, no 9 (septembre 2007) : 617–20. http://dx.doi.org/10.1109/lsp.2007.894966.

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Okumura, Miwa, Takamasa Ota, Kazuhisa Kainuma, James W. Sayre, Michael McNitt-Gray et Kazuhiro Katada. « Effect of Edge-Preserving Adaptive Image Filter on Low-Contrast Detectability in CT Systems : Application of ROC Analysis ». International Journal of Biomedical Imaging 2008 (2008) : 1–6. http://dx.doi.org/10.1155/2008/379486.

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Objective. For the multislice CT (MSCT) systems with a larger number of detector rows, it is essential to employ dose-reduction techniques. As reported in previous studies, edge-preserving adaptive image filters, which selectively eliminate only the noise elements that are increased when the radiation dose is reduced without affecting the sharpness of images, have been developed. In the present study, we employed receiver operating characteristic (ROC) analysis to assess the effects of the quantum denoising system (QDS), which is an edge-preserving adaptive filter that we have developed, on low-contrast resolution, and to evaluate to what degree the radiation dose can be reduced while maintaining acceptable low-contrast resolution.Materials and Methods. The low-contrast phantoms (Catphan 412) were scanned at various tube current settings, and ROC analysis was then performed for the groups of images obtained with/without the use of QDS at each tube current to determine whether or not a target could be identified. The tube current settings for which the area under the ROC curve (Az value) was approximately 0.7 were determined for both groups of images with/without the use of QDS. Then, the radiation dose reduction ratio when QDS was used was calculated by converting the determined tube current to the radiation dose.Results. The use of the QDS edge-preserving adaptive image filter allowed the radiation dose to be reduced by up to 38%.Conclusion. The QDS was found to be useful for reducing the radiation dose without affecting the low-contrast resolution in MSCT studies.
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Bhattacharjee, Debjyoti, Ashish Bakshi et Kuntal Ghosh. « Comparison Between an HVS Inspired Linear Filter and the Bilateral Filter in Performing "Vision at a Glance" through Smoothing with Edge Preservation ». International Journal of Image and Graphics 15, no 04 (12 août 2015) : 1550015. http://dx.doi.org/10.1142/s0219467815500151.

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We propose that the Magno (M)-channel filter, belonging to the extended classical receptive field (ECRF) model, provides us with "vision at a glance", by performing smoothing with edge preservation. We compare the performance of the M-channel filter with the well-known bilateral filter in achieving such "vision at a glance" which is akin to image preprocessing in the computer vision domain. We find that at higher noise levels, the M-channel filter performs better than the bilateral filter in terms of reducing noise while preserving edge details. The M-channel filter is also significantly simpler and therefore faster than the bilateral filter. Overall, the M-channel filter enables us to model, simulate and arrive at a better understanding of some of the initial mechanisms in visual pathway, while simultaneously providing a fast, biologically inspired algorithm for digital image preprocessing.
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Jayanthi Sree, S., et C. Vasanthanayaki. « De-Speckling of Ultrasound Images Using Local Statistics-Based Trilateral Filter ». Journal of Circuits, Systems and Computers 28, no 09 (août 2019) : 1950150. http://dx.doi.org/10.1142/s0218126619501500.

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Speckle noise in ultrasound images is a major hindrance for the automation of segmentation, detection, classification and measurements of region of interest, to assist clinician for diagnosing pathologies. Speckle noise occurs due to constructive and destructive interference of the echo signals reflected from the target and has a granular appearance. Various techniques have been devised for speckle reduction. Most of these techniques are based on adaptive filters, wavelet transform and anisotropic diffusion filters. In this paper, a new speckle reduction technique based on the trilateral filter and local statistics of the image has been developed. The local speckle content of the image influences the trilateral filtering. The trilateral filter is a robust edge preserving filter which considers the similarity of neighboring regions in terms of adjacency, intensity and edge details. Hence, the new method preserves the finer details of the ultrasound images in the process of filtering speckle noise. The proposed technique is validated using synthetic, simulated and real-time clinical ultrasound images. Comparison of the proposed technique with the existing speckle removal algorithms in terms of quality metrics such as MSE, PSNR, UQI, SSI, FoM has been made and best results are obtained for the proposed technique.
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Srisuk, Sanun, Wachirapong Kesjindatanawaj et Surachai Ongkittikul. « Real-Time Bilateral Filtering Using GPGPU ». Applied Mechanics and Materials 781 (août 2015) : 568–71. http://dx.doi.org/10.4028/www.scientific.net/amm.781.568.

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In this paper, we present a technique for accelerating the bilateral filtering using GPGPU. Bilateral filtering is a tool for an image smoothing with edge preserving properties. It serves as a mixture of domain and range filters. Domain filter suppresses Gaussian noise while range filter maintains sharp edges. Bilateral filtering is a nonlinear filtering in which the filter kernel must be computed pixel by pixel. Therefore conventional fast Fourier transform technique cannot be used to accelerate the bilateral filtering. Instead, general purpose GPU is used as a parallel machine to reduce time consuming of the bilateral filtering. We will show the experimental results by comparing the computation time of CPU and GPU. It was cleared that, from the experimental results, GPU outperformed the CPU in terms of computation time.
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Dash, Sonali, Sahil Verma, Kavita, N. Z. Jhanjhi, Mehedi Masud et Mohammed Baz. « Curvelet Transform Based on Edge Preserving Filter for Retinal Blood Vessel Segmentation ». Computers, Materials & ; Continua 71, no 2 (2022) : 2459–76. http://dx.doi.org/10.32604/cmc.2022.020904.

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Vinh, Truong Quang, Ji-Hoon Kim et Young-Chul Kim. « Deblocking Filter Based on Edge-Preserving Algorithm And an Efficient VLSI Architecture ». Journal of Korea Information and Communications Society 36, no 11C (30 novembre 2011) : 662–72. http://dx.doi.org/10.7840/kics.2011.36c.11.662.

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Suryanarayana, Gunnam, et Ravindra Dhuli. « Edge preserving super-resolution algorithm using multi-stage cascaded joint bilateral filter ». International Journal of Modeling, Simulation, and Scientific Computing 08, no 01 (10 janvier 2017) : 1750003. http://dx.doi.org/10.1142/s1793962317500039.

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Super-resolution (SR) algorithms address the inabilities of poor imaging devices, there by producing high quality images with enhanced resolution. We propose a new SR approach which produces sharp high resolution (HR) image using its low resolution (LR) counterparts. The proposed method uses geometric duality for spatially adapting covariance-based interpolation (CBI). To preserve edge information, a multi-stage cascaded joint bilateral filter (MSCJBF) is proposed as an intermediary stage. These edges are incorporated in the high frequency subbands obtained by the stationary wavelet transform (SWT), through nearest neighbor interpolation (NNI) method. Prior to the NNI process, the high frequency subbands undergo two-lobed lanczos interpolation to achieve the desired resolution enhancement. The quantitative and qualitative analysis for various test images prove the superiority of our method.
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Liu, Wei, Pingping Zhang, Xiaogang Chen, Chunhua Shen, Xiaolin Huang et Jie Yang. « Embedding Bilateral Filter in Least Squares for Efficient Edge-Preserving Image Smoothing ». IEEE Transactions on Circuits and Systems for Video Technology 30, no 1 (janvier 2020) : 23–35. http://dx.doi.org/10.1109/tcsvt.2018.2890202.

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Alparone, Luciano, et Andrea Garzelli. « Decimated geometric filter for edge-preserving smoothing of non-white image noise ». Pattern Recognition Letters 19, no 1 (mai 1998) : 89–96. http://dx.doi.org/10.1016/s0167-8655(97)00157-8.

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Aleardi, Mattia. « Including edge preserving smoothing filter within blocky- constrained, target-oriented AVA inversions ». Journal of Applied Geophysics 169 (octobre 2019) : 15–28. http://dx.doi.org/10.1016/j.jappgeo.2019.06.015.

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Zhu, Zhu, Xiaoguo Zhang, Qing Wang, Xueyin Wan et Yanchang Xiao. « Edge-Preserving Regularized Filter with Spatial Local Outlier Measure and Q-Estimate ». Circuits, Systems, and Signal Processing 33, no 2 (14 août 2013) : 629–42. http://dx.doi.org/10.1007/s00034-013-9644-x.

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