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Journal articles on the topic 'Speckle Filter'

Author: Grafiati

Published: 3 June 2025

Last updated: 1 August 2025

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1

Hu, J., R. Guo, X. Zhu, G. Baier, and Y. Wang. "NON-LOCAL MEANS FILTER FOR POLARIMETRIC SAR SPECKLE REDUCTION-EXPERIMENTS USING TERRASAR-X DATA." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences II-3/W4 (March 11, 2015): 71–77. http://dx.doi.org/10.5194/isprsannals-ii-3-w4-71-2015.

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The speckle is omnipresent in synthetic aperture radar (SAR) images as an intrinsic characteristic. However, it is unwanted in certain applications. Therefore, intelligent filters for speckle reduction are of great importance. It has been demonstrated in several literatures that the non-local means filter can reduce noise while preserving details. This paper discusses non-local means filter for polarimetric SAR (PolSAR) speckle reduction. The impact of different similarity approaches, weight kernels, and parameters in the filter were analysed. A data-driven adaptive weight kernel was proposed.

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Bonny, Sarungbam, and Yambem Jina Chanu. "Speckle Reduction in SAR Images by Using Homogeneity NeighShrink." European Journal of Engineering and Technology Research 1, no. 4 (2018): 9–14. http://dx.doi.org/10.24018/ejeng.2016.1.4.176.

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Synthetic Aperture Radar (SAR) image suffers from severe artifacts caused by speckle noise which is multiplicative in nature. Some of the adaptive filters such as the Lee filter, the Frost filter and the Kuan filter are the well known speckle filters. These filters adapt the filter coefficients based on the pixels within a fixed moving window. Though it removes speckle noise well in the homogeneous regions, it leaves noise in the heterogeneous areas to preserve the edges and fine details or smoothes the edges to remove the noise in this area. In order to reduce the speckle noise with the prese

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Jayanthi Sree, S., and C. Vasanthanayaki. "De-Speckling of Ultrasound Images Using Local Statistics-Based Trilateral Filter." Journal of Circuits, Systems and Computers 28, no. 09 (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 filte

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Tuzova, A. A., V. A. Pavlov, and A. A. Belov. "Reduction of Multiplicative Noise in Radar Images." Journal of the Russian Universities. Radioelectronics 24, no. 4 (2021): 6–18. http://dx.doi.org/10.32603/1993-8985-2021-24-4-6-18.

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Introduction. A radar image is an image obtained by remote sensing the earth's surface with a radar device. Radar images are characterized by background graininess caused by speckle noise, which should be filtered to improve the quality of radar images. The structure of speckle noise reduction filters often comprise one or more parameters to control the level of noise smoothing. The values of these parameters have to be selected experimentally. In works devoted to speckle noise filtering, the methods used for selecting filter paraments are rarely clarified.Aim. To present a methodology for sel

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Aessa, Suad Ali, Ekbal Hussain Ali, Salam Waley Shneen, and Layla H. Abood. "Adaptive Fuzzy Filter Technique for Mixed Noise Removing from Sonar Images Underwater." Journal of Fuzzy Systems and Control 2, no. 2 (2024): 45–49. https://doi.org/10.59247/jfsc.v2i2.176.

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Underwater Analysis of acquired images may be affected by low contrast, haze, and other disturbances., caused by scattering and absorption of the light through propagation. An adaptive fuzzy filter for three mixed noise reduction is adopted on underwater sonar images to take out the various noises that either appear in the image when captured or injected into the image when transmitted. Underwater images when captured usually have speckle noise, salt, pepper noise also Gaussian noise. Is suggested in this paper an adaptive fuzzy filter structure that combines the fuzzy filter, sigmoid sliding

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Guo, Fei, Mei Zhao, Xiu Ying Fan, Jin He Bao, and Wen Bang Sun. "Filtering of Electronic Speckle Correlation Fringes." Applied Mechanics and Materials 198-199 (September 2012): 1202–7. http://dx.doi.org/10.4028/www.scientific.net/amm.198-199.1202.

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Speckle correlation fringes include a large quantity of speckle noise. It is first to consider how to reduce speckle noise before using phase formula to calculate. Filter is usually used to reduce speckle noise. From two aspects of frequency domain and space domain, we adopted mean filter, medium filter, Butterworth low-pass filter and homomorphism filter to process the speckle correlation fringes obtained by experiment. It is shown that the speckle correlation fringes are clearer and more easily interpreted and automatic processed after being filtered.

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Biradar, Nagashettappa, M. L. Dewal, and Manoj Kumar Rohit. "Edge Preserved Speckle Noise Reduction Using Integrated Fuzzy Filters." International Scholarly Research Notices 2014 (October 30, 2014): 1–11. http://dx.doi.org/10.1155/2014/876434.

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Echocardiographic images are inherent with speckle noise which makes visual reading and analysis quite difficult. The multiplicative speckle noise masks finer details, necessary for diagnosis of abnormalities. A novel speckle reduction technique based on integration of geometric, wiener, and fuzzy filters is proposed and analyzed in this paper. The denoising applications of fuzzy filters are studied and analyzed along with 26 denoising techniques. It is observed that geometric filter retains noise and, to address this issue, wiener filter is embedded into the geometric filter during iteration

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Ueng, Shyh-Kuang, Cho-Li Yen, and Guan-Zhi Chen. "Ultrasound Image Enhancement Using Structure-Based Filtering." Computational and Mathematical Methods in Medicine 2014 (2014): 1–14. http://dx.doi.org/10.1155/2014/758439.

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Ultrasound images are prone to speckle noises. Speckles blur features which are essential for diagnosis and assessment. Thus despeckling is a necessity in ultrasound image processing. Linear filters can suppress speckles, but they smooth out features. Median filter based despeckling algorithms produce better results. However, they may produce artifact patterns in the resulted images and oversmooth nonuniform regions. This paper presents an innovative despeckle procedure for ultrasound images. In the proposed method, the diffusion tensor of intensity is computed at each pixel at first. Then the

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Ristau, J. P., and Wooil M. Moon. "Adaptive filtering of random noise in 2-D geophysical data." GEOPHYSICS 66, no. 1 (2001): 342–49. http://dx.doi.org/10.1190/1.1444913.

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Random noise is often a problem in geophysical data visualization because it obscures fine details and complicates identification of image features. Adaptive filters have recently been used to suppress speckle (random) noise in synthetic aperture radar (SAR) images. SAR data are similar to seismic reflection data, both in their data acquisition approach and in their final data processed format. The nature of the random noise associated is also very similar, and adaptive filters can be applied to reduce random noise in both types of data sets. In this paper several popular adaptive filters—the

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Singh, Prabhishek, Ankur Maurya, Achyut Shankar, Sathishkumar V. E., and Manoj Diwakar. "A Review on Speckle Reduction Techniques in SAR images." Applied and Computational Engineering 8, no. 1 (2023): 714–20. http://dx.doi.org/10.54254/2755-2721/8/20230069.

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Synthetic Aperture Radar (SAR) is satellite imagery that has multiple applications in variegated fields but is often corrupted by single dependent multiplicative speckle noise. Its multiplicative nature decreases scope for image perception, recognition & limits SAR images applications. Thus, increasing the need for effective & astute SAR image despeckling techniques that not only excise speckle noise but also preserve SAR imageries features, details, and resolution quality. This study analyses various research literature & techniques namely, Adaptive Speckle Reduction Filter, Condi

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Zayed, M. Ramadan. "Optimum Image Filters for Various Types of Noise." TELKOMNIKA Telecommunication, Computing, Electronics and Control 16, no. 5 (2018): 2458–64. https://doi.org/10.12928/TELKOMNIKA.v16i5.10508.

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In this paper, the quality performance of several filters in restoration of images corrupted with various types of noise has been examined extensively. In particular, Wiener filter, Gaussian filter, median filter and averaging (mean) filter have been used to reduce Gaussian noise, speckle noise, salt and pepper noise and Poisson noise. Many images have been tested, two of which are shown in this paper. Several percentages of noise corrupting the images have been examined in the simulations. The size of the sliding window is the same in the four filters used, namely 5x5 for all the indicated no

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Rose, Jemila R., and S. Allwin. "Speckle Suppressing Improved Oriented Speckle Reducing Anisotropic Diffusion (IOSRAD) Filter for Medical Ultrasound Images." Applied Mechanics and Materials 626 (August 2014): 106–10. http://dx.doi.org/10.4028/www.scientific.net/amm.626.106.

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— Ultrasound imaging is the most commonly used imaging system in medical field. Main problem related to this imaging technique is introduction of speckle noise, thus making the image unclear. The success of ultrasonic examination depends on the image quality which is usually retarded due to speckle noise. There have been several techniques for effective suppression of speckle noise present in ultrasound images. The filtering techniques considered include anisotropic diffusion, wavelet de-noising, and local statistics. Comparison of the filters is based on their application of objective quality

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Kumar, Nalin, and M. Nachamai. "Noise Removal and Filtering Techniques used in Medical Images." Oriental journal of computer science and technology 10, no. 1 (2017): 103–13. http://dx.doi.org/10.13005/ojcst/10.01.14.

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Noise removal techniques have become an essential practice in medical imaging application for the study of anatomical structure and image processing of MRI medical images. To report these issues many de-noising algorithm has been developed like Weiner filter, Gaussian filter, median filter etc. In this research work is done with only three of the above filters which are already mentioned were successfully used in medical imaging. The most commonly affected noises in medical MRI image are Salt and Pepper, Speckle, Gaussian and Poisson noise. The medical images taken for comparison include MRI i

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Ali, Ekbal Hussain, Ahmed Hameed Reja, and Layla H. Abood. "Design hybrid filter technique for mixed noise reduction from synthetic aperture radar imagery." Bulletin of Electrical Engineering and Informatics 11, no. 3 (2022): 1325–31. http://dx.doi.org/10.11591/eei.v11i3.3708.

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For military and civilian applications, synthetic aperture radar (SAR) imaging is an essential instrument for obtaining images of the Earth's surface. Speckle noise, a form of noise that is multiplicative, generated by conflicting echoes returned from each pixel, has a significant impact on the SAR picture. On SAR pictures, a hybrid filter for mixed noise reduction is used to remove the mixed noises that are present in the data during capture and transmission. Specifically, speckle noise and salt and pepper noises from SAR images. Both are being worked on at the same time to minimize mixed noi

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Ekbal, Hussain Ali, Hameed Reja Ahmed, and H. Abood Layla. "Design hybrid filter technique for mixed noise reduction from synthetic aperture radar imagery." Bulletin of Electrical Engineering and Informatics 11, no. 3 (2022): 1325~1331. https://doi.org/10.11591/eei.v11i3.3708.

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For military and civilian applications, synthetic aperture radar (SAR) imaging is an essential instrument for obtaining images of the Earth's surface. Speckle noise, a form of noise that is multiplicative, generated by conflicting echoes returned from each pixel, has a significant impact on the SAR picture. On SAR pictures, a hybrid filter for mixed noise reduction is used to remove the mixed noises that are present in the data during capture and transmission. Specifically, speckle noise and salt and pepper noises from SAR images. Both are being worked on at the same time to minimize mixed

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Sribi, M. P* Mredhula L. "NON-LINEAR THRESHOLDING DIFFUSION METHOD FOR SPECKLE NOISE REDUCTION IN ULTRASOUND IMAGES." Global Journal of Engineering Science and Research Management 5, no. 9 (2018): 62–67. https://doi.org/10.5281/zenodo.1435379.

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Ultrasound (US) medical images are very important tools in modern medicine used for the diagnosis and study of various illnesses. Speckle is the important phenomenon that affects the quality of ultrasound images. This paper presents a new speckle suppression method in US images. The idea is based on the combination of different filters in serial as well as parallel form. The speckle noise affected image is separated into two parts using adaptive weighted median filter. These two parts are then filtered using wavelet transform and the wavelet coefficients are processed with soft thresholding. T

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CHEREPANOV, ILLIA. "INVESTIGATION OF DIFFERENT METHODS OF THRESHOLD SELECTION FOR DCT-SSA FILTER." Herald of Khmelnytskyi National University. Technical sciences 349, no. 2 (2025): 458–65. https://doi.org/10.31891/2307-5732-2025-349-67.

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Synthetic aperture radars (SARs) are used to acquire images that are employed for a variety of practical applications, from analyzing soil and vegetation cover to searching for large accumulations of illegally dumped debris. The problem of processing such images is that the obtained images are spoiled by speckle - a noise-like effect with multiplicative nature. Also, speckle has a non-Gaussian distribution and is spatially correlated. To address this problem, many filters have been developed that take into account the non-Gaussianity of the distribution and also provide acceptable speckle supp

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Sun, Z., and Y. Song. "STRUCTURAL INFORMATION DETECTION BASED FILTER FOR GF-3 SAR IMAGES." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3 (April 30, 2018): 1617–21. http://dx.doi.org/10.5194/isprs-archives-xlii-3-1617-2018.

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GF-3 satellite with high resolution, large swath, multi-imaging mode, long service life and other characteristics, can achieve allweather and all day monitoring for global land and ocean. It has become the highest resolution satellite system in the world with the C-band multi-polarized synthetic aperture radar (SAR) satellite. However, due to the coherent imaging system, speckle appears in GF-3 SAR images, and it hinders the understanding and interpretation of images seriously. Therefore, the processing of SAR images has big challenges owing to the appearance of speckle. The high-resolution SA

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Verhoeven, J. T. M., and J. M. Thijssen. "Improvement of Lesion Detectability by Speckle Reduction Filtering: A Quantitative Study." Ultrasonic Imaging 15, no. 3 (1993): 181–204. http://dx.doi.org/10.1177/016173469301500301.

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An objective measure (Lesion Signal-to-Noise Ratio) quantifying the detectability of lesions in echographic images was employed. This measure was used to determine the performance of digital speckle reduction filters, which were applied to computer simulated ultrasound B-mode images. One linear (mean filter) and two nonlinear filters (median and L2-mean filters) have been investigated. A comparison was made between fixed and adaptive versions of these filters. The influence of the size of the filter window on the Lesion Signal-to-Noise Ratio was systematically investigated. Also, the effect of

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Chan, Debora, Juliana Gambini, and Alejandro C. Frery. "Entropy-Based Non-Local Means Filter for Single-Look SAR Speckle Reduction." Remote Sensing 14, no. 3 (2022): 509. http://dx.doi.org/10.3390/rs14030509.

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Speckle is an interference phenomenon that contaminates images captured by coherent illumination systems. Due to its multiplicative and non-Gaussian nature, it is challenging to eliminate. The non-local means approach to noise reduction has proven flexible and provided good results. We propose in this work a new non-local means filter for single-look speckled data using the Shannon and Rényi entropies under the G0 model. We obtain the necessary mathematical apparatus (the Fisher information matrix and asymptotic variance of maximum likelihood estimators). The similarity between samples of the

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Zhang, Haiyue, Daoyun Xu, and Yongbin Qin. "Weighted Image Averaging Based Anisotropic Diffusion Denoising Method for Ultrasound Thyroid Image." Journal of Medical Imaging and Health Informatics 10, no. 2 (2020): 380–90. http://dx.doi.org/10.1166/jmihi.2020.2902.

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Thyroid disease is a frequent occurrence in clinical practice and the computerized analysis of ultrasonography has been becoming the most prospective tool for thyroid disease automatic diagnosis. However, the accuracy of vision-based diagnostic analysis is often reduced because the quality of ultrasound image is easily corrupted by the speckle noise. Thus, noise suppression is imperative and significant for the thyroid ultrasonography image preprocessing to increase the reliability of subsequent analysis. In this paper, we propose a novel weighted image averaging method based on anisotropic di

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Heidarpour Shahrezaei, Iman, and Hyun-cheol Kim. "Resolutional Analysis of Multiplicative High-Frequency Speckle Noise Based on SAR Spatial De-Speckling Filter Implementation and Selection." Remote Sensing 11, no. 9 (2019): 1041. http://dx.doi.org/10.3390/rs11091041.

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Due to the inherent characteristics of the electromagnetic wave scattering phenomenon, synthetic aperture radar (SAR) images are directly degraded by high-frequency multiplicative speckle (HMS) noise, which makes image de-speckling filter application and selection a challenge. In this regard, an adverse effects analysis of the HMS under implementation of seven different spatial de-speckling filters on a reference SAR image is considered in this paper. The investigation includes the formulation of the backscattered data and the HMS based on the pixel statistics and their distribution as an imag

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Takahashi, Yoshitaka, Takaya Okada, Ryutaro Sekiguchi, and Madoka Fukushima. "Noise Filter Reducing Deformation in Digital Holography." Advanced Engineering Forum 38 (November 2020): 71–75. http://dx.doi.org/10.4028/www.scientific.net/aef.38.71.

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A phase difference image using phase-shifting digital holography, which is applied for non-contact shape measurement, contains speckle noises and filtering to reduce them is inevitable for its application. We have developed a new filter which causes less deformation than commonly used filters.

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Crimmins, Thomas R. "Geometric Filter For Reducing Speckle." Optical Engineering 25, no. 5 (1986): 255651. http://dx.doi.org/10.1117/12.7973879.

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Crimmins, Thomas R. "Geometric filter for speckle reduction." Applied Optics 24, no. 10 (1985): 1438. http://dx.doi.org/10.1364/ao.24.001438.

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Ma, Run Xia, Xu Ming Zhang, Ming Yue Ding, and Qi Liu. "Comparative Study on Filter Methods of Medical Ultrasound Images." Advanced Materials Research 341-342 (September 2011): 467–71. http://dx.doi.org/10.4028/www.scientific.net/amr.341-342.467.

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This paper presents a comparative study on six despeckling methods such as modified hybrid median filter, gabor filter, speckle reducing anisotropic diffusion, homomorphic filter, non-local mean filter and squeeze box filter. We select eight objective evaluation parameters, such as signal-to-ratio, contrast signal–to–noise ratio, figure of merit, least absolute error, peak signal-to-noise ratio, edge protection factor, quantitative parameters of despeckling, signal-to-minimum mean square error ratio, to quantify the performance of these filters. The comparative study will provide a good guidan

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Bhardwaj, Ankur, Sanmukh Kaur, Anand Prakash Shukla, and Manoj Kumar Shukla. "A Novel Method for Despeckling of Ultrasound Images Using Cellular Automata-Based Despeckling Filter." International Journal of E-Health and Medical Communications 12, no. 5 (2021): 16–35. http://dx.doi.org/10.4018/ijehmc.20210901.oa2.

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Ultrasound images have an inherent property termed as speckle noise that is the outcome of interference between incident and reflected ultrasound waves which reduce image resolution and contrast and could lead to improper diagnosis of any disease. In different approaches for reducing the speckle noise, there exists a class of filters that convert multiplicative noise into additive noise by using algorithmic functions. The current study proposes a cellular automata-based despeckling filter (CABDF) that implements a local spatial filtering framework for the restoration of the noisy image. In the

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Lestari, Anugrah I., Dony Kushardono, and Athar A. Bayanuddin. "Burned area detection using convolutional neural network based on spatial information of synthetic aperture radar data in Indonesia." GEOGRAPHY, ENVIRONMENT, SUSTAINABILITY 17, no. 2 (2024): 36–48. http://dx.doi.org/10.24057/2071-9388-2024-3109.

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Forest and land fires are disasters that often occur in Indonesia which affects neighbouring countries. The burned area can be observed using remote sensing. Synthetic aperture radar (SAR) sensor data is advantageous since it can penetrate clouds and smoke. However, image analysis of SAR data differs from optical data, which is based on properties such as intensity, texture, and polarimetric feature. This research aims to propose a method to detect burned areas from the extracted feature of Sentinel-1 data. The features were classified using the Convolutional Neural Network (CNN) classifier. T

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Chen, Wu Fen, Ai Lian Liu, Jia Jia Xia, Chao Lei Duan, Song Song Yang, and Wan Ceng Hu. "Study on Synthetic Aperture Radar Image Denoising Algorithm." Applied Mechanics and Materials 599-601 (August 2014): 1734–37. http://dx.doi.org/10.4028/www.scientific.net/amm.599-601.1734.

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In synthetic aperture radar (SAR) inherent speckle will affect the legibility of image details; give the image target detection adverse effects. In order to reduce the SAR image speckles noise, this article provided an improved algorithm based on median filter and wavelet semi-soft threshold shrinkage. First, reduced the SAR image speckle with median filtering method, then, with the filtered image, filtering the image with wavelet half soft threshold value contraction algorithm to noise, Simulation results show that the algorithm based on median filtering and improved algorithm of wavelet half

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Mohan, Ramya, S. P. Chokkalingam, Kirupa Ganapathy, and A. Rama. "Comparative Image Quality Analysis of Spatial Filters for Pre-processing of CT Abdominal Images." Webology 18, Special Issue 04 (2021): 1449–69. http://dx.doi.org/10.14704/web/v18si04/web18283.

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Aim: To determine the efficient noise reduction filter for abdominal CT images. Background: Image enrichment is the first and foremost step that has to be done in all image processing applications. It is used to enhance the quality of digital images. Digital images are liable to addition of noise from various sources such as error in instrument calibration, excess staining of images, etc., Image de-noising is an enhancement technique used to remove / reduce noise present in an image. Reducing the noise of images and preserving its edges are always critical and challenging in image processing.

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Rakotomamonjy, Alain, Philippe Deforge, and Pierre Marché. "Wavelet-Based Speckle Noise Reduction in Ultrasound B-Scan Images." Ultrasonic Imaging 22, no. 2 (2000): 73–94. http://dx.doi.org/10.1177/016173460002200201.

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Speckle noise is known to be signal-dependent in ultrasound imaging. Hence, separating noise from signal becomes a difficult task. This paper describes a wavelet-based method for reducing speckle noise. We derive from the model of the displayed ultrasound image the optimal wavelet-domain filter, in the least mean-square sense. Simulations on synthetic data have been carried out in order to assess the performance of the proposed filter with regards to the classical wavelet shrinkage scheme, while phantom and tissue images have been used for testing it on real data. The results show that the fil

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Wang, Li, Zhenling Yang, Yi-Fei Pu, Hao Yin, and Xuexia Ren. "An Efficient Multi-Scale Wavelet Approach for Dehazing and Denoising Ultrasound Images Using Fractional-Order Filtering." Fractal and Fractional 8, no. 9 (2024): 549. http://dx.doi.org/10.3390/fractalfract8090549.

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Ultrasound imaging is widely used in medical diagnostics due to its non-invasive and real-time capabilities. However, existing methods often overlook the benefits of fractional-order filters for denoising and dehazing. Thus, this work introduces an efficient multi-scale wavelet method for dehazing and denoising ultrasound images using a fractional-order filter, which integrates a guided filter, directional filter, fractional-order filter, and haze removal to the different resolution images generated by a multi-scale wavelet. In the directional filter stage, an eigen-analysis of each pixel is c

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Gunadi, I. Gede Aris. "ANALISIS PERBANDINGAN METODE FILTER MEAN, MEDIAN, MAXIMUM, MINIMUM, DAN GAUSSIAN TERHADAP REDUKSI NOISE GAUSSIAN, SALT&PAPPER , SPECKLE, POISSON, DAN LOCALVAR." Jurnal Ilmiah SINUS 17, no. 1 (2019): 15. http://dx.doi.org/10.30646/sinus.v17i1.392.

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Due to the influence of noise on an image, the image will experience a decrease in quality. If the type of noise is known for certain, then the right solution can be determined to restore the condition of an image so that the condition returns to normal. The effort to restore the image condition is stated by image restoration. The most important thing in image restoration is determining the type of noise and the solution for the noise.In this study several types of noise were tried, gaussian, salt & paper, speckle, poisson, and Localvar on several image samples. In the image that had been

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Huo, Fu Rong, He Li, Yu Hang Yang, Chang Xi Xue, and Wen Sheng Wang. "Imaging Analysis and Application of Digital Speckle Photography with EALCD." Applied Mechanics and Materials 333-335 (July 2013): 1007–12. http://dx.doi.org/10.4028/www.scientific.net/amm.333-335.1007.

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According to the principle of speckle photography, CCD(Charge-Coupled Device) as a recorder, and EALCD(Electrically Addressed Liquid Crystal Display) as a read-out element, which makes the speckle photography to digital. Recording light path of the subjective and the objective speckle and observation light path of full-field analysis and point-by-point analysis for fringe reconstruction have been respectively researched. At the same time, measuring by speckle photography, the fringes in the interometry pattern must be carefully analyzed. Since the speckle noise can greatly infect the signals.

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Choi, Hyunho, and Jechang Jeong. "Speckle Noise Reduction Technique for SAR Images Using Statistical Characteristics of Speckle Noise and Discrete Wavelet Transform." Remote Sensing 11, no. 10 (2019): 1184. http://dx.doi.org/10.3390/rs11101184.

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Synthetic aperture radar (SAR) images map Earth’s surface at high resolution, regardless of the weather conditions or sunshine phenomena. Therefore, SAR images have applications in various fields. Speckle noise, which has the characteristic of multiplicative noise, degrades the image quality of SAR images, which causes information loss. This study proposes a speckle noise reduction algorithm while using the speckle reducing anisotropic diffusion (SRAD) filter, discrete wavelet transform (DWT), soft threshold, improved guided filter (IGF), and guided filter (GF), with the aim of removing speckl

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Purwanti Ningrum, Ika, Agfianto Eko Putra, and Dian Nursantika. "Penapisan Derau Gaussian, Speckle dan Salt&Pepper Pada Citra Warna." IJCCS (Indonesian Journal of Computing and Cybernetics Systems) 5, no. 3 (2011): 29. http://dx.doi.org/10.22146/ijccs.5209.

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Quality of digital image can decrease becouse some noises. Noise can come from lower quality of image recorder, disturb when transmission data process and weather. Noise filtering can make image better becouse will filtering that noise from the image and can improve quality of digital image. This research have aim to improve color image quality with filtering noise. Noise (Gaussian, Speckle, Salt&Pepper) will apply to original image, noise from image will filtering use Bilateral Filter method, Median Filter method and Average Filter method so can improve color image quality. To know how we

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Anam, S., E. Uchino, and N. Suetake. "Coronary Plaque Boundary Enhancement in IVUS Image by Using a Modified Perona-Malik Diffusion Filter." International Journal of Biomedical Imaging 2014 (2014): 1–9. http://dx.doi.org/10.1155/2014/740627.

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We propose a modified Perona-Malik diffusion (PMD) filter to enhance a coronary plaque boundary by considering the conditions peculiar to an intravascular ultrasound (IVUS) image. The IVUS image is commonly used for a diagnosis of acute coronary syndrome (ACS). The IVUS image is however very grainy due to heavy speckle noise. When the normal PMD filter is applied for speckle noise reduction in the IVUS image, the coronary plaque boundary becomes vague. For this problem, we propose a modified PMD filter which is designed in special reference to the coronary plaque boundary detection. It can the

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Zayed, M. Ramadan. "Effect of kernel size on Wiener and Gaussian image filtering." TELKOMNIKA Telecommunication, Computing, Electronics and Control 17, no. 3 (2019): 1455–60. https://doi.org/10.12928/TELKOMNIKA.v17i3.11192.

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In this paper, the effect of the kernel size of Wiener and Gaussian filters on their image restoration qualities has been studied and analyzed. Four sizes of such kernels, namely 3x3, 5x5, 7x7 and 9x9 were simulated. Two different types of noise with zero mean and several variances have been used: Gaussian noise and speckle noise. Several image quality measuring indices have been applied in the computer simulations. In particular, mean absolute error (MAE), mean square error (MSE) and structural similarity (SSIM) index were used. Many images were tested in the simulations; however the results

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Lopez-Martinez, Carlos, and Xavier Fabregas. "Model-Based Polarimetric SAR Speckle Filter." IEEE Transactions on Geoscience and Remote Sensing 46, no. 11 (2008): 3894–907. http://dx.doi.org/10.1109/tgrs.2008.2002029.

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Afsham, Narges, Abtin Rasoulian, Mohammad Najafi, Purang Abolmaesumi, and Robert Rohling. "Nonlocal means filter-based speckle tracking." IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control 62, no. 8 (2015): 1501–15. http://dx.doi.org/10.1109/tuffc.2015.007134.

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Sharma, Rakesh, and Rajib Kumar Panigrahi. "CFAR-Based Adaptive PolSAR Speckle Filter." IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 11, no. 12 (2018): 4895–905. http://dx.doi.org/10.1109/jstars.2018.2877670.

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Chun-ming, HAN, GUO Hua-dong, WANG Chang-lin, and FAN Dian. "An Enhanced SAR Image Speckle Filter." National Remote Sensing Bulletin, no. 2 (2004): 121–27. http://dx.doi.org/10.11834/jrs.20040205.

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C, Shankara, and A. Hariprasad S. "Noise Removal Techniques for Lung Cancer CT Images." Indian Journal of Science and Technology 15, no. 32 (2022): 1577–86. https://doi.org/10.17485/IJST/v15i32.798.

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Abstract <strong>Objectives:</strong> To analyze various filtering methods to eliminate noises present in the lung CT images and to enhance the image, which help in further evaluation of CT images for accurate lung cancer detection. To compare the proposed method with existing filtering techniques and to find the best filtering technique. <strong>Methods:</strong> For input lung CT images noises like salt along with pepper noise and speckle noise are added. For noisy images different filtering methods like Median filter, Wiener filter, Gaussian filter and Guided filter are appli

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Damdinsuren, Amarsaikhan, Enkhjargal Damdinsuren, and Tsogzol Gurjav. "A comparison of filters to remove speckle from radar data." Mongolian Journal of Geography and Geoecology 61, no. 45 (2024): 89–97. https://doi.org/10.5564/mjgg.v61i45.3367.

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Regardless of the natural and climate conditions of a given area, it is possible to conduct mapping using radar remote sensing both during the day and at night. Compared to passive remote sensing, active or radar remote sensing emits short waves from an antenna at a slanting angle. Due to the coherent nature of radar waves, the waves scattered from the Earth’s objects close to each other often coincide, creating black and white spots on the image due to the phase difference of the waves. These speckles make interpretation and analysis of the image difficult. To reduce the speckle, various spec

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Ma, Xiaoshuang, and Penghai Wu. "Multitemporal SAR Image Despeckling Based on a Scattering Covariance Matrix of Image Patch." Sensors 19, no. 14 (2019): 3057. http://dx.doi.org/10.3390/s19143057.

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This paper presents a despeckling method for multitemporal images acquired by synthetic aperture radar (SAR) sensors. The proposed method uses a scattering covariance matrix of each image patch as the basic processing unit, which can exploit both the amplitude information of each pixel and the phase difference between any two pixels in a patch. The proposed filtering framework consists of four main steps: (1) a prefiltering result of each image is obtained by a nonlocal weighted average using only the information of the corresponding time phase; (2) an adaptively temporal linear filter is empl

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Yang, Xiu Jie, and Ping Chen. "SAR Image Denoising Algorithm Based on Bayes Wavelet Shrinkage and Fast Guided Filter." Journal of Advanced Computational Intelligence and Intelligent Informatics 23, no. 1 (2019): 107–13. http://dx.doi.org/10.20965/jaciii.2019.p0107.

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To remove the speckle noise of synthetic aperture radar (SAR) images, a novel denoising algorithm based on Bayes wavelet shrinkage and a fast guided filter is proposed. According to the statistical properties of SAR images, the noise-free signal and speckle noise in the wavelet domain are modeled as Laplace and Fisher-Tippett distributions respectively. Then a new wavelet shrinkage algorithm is obtained by adopting the Bayes maximum a posteriori estimation. Speckle noise in the high-frequency domain of SAR images is shrunk by this new wavelet shrinkage algorithm. As the wavelet coefficients of

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Li, Hui, and Xu-Liang Duan. "SAR Ship Image Speckle Noise Suppression Algorithm Based on Adaptive Bilateral Filter." Wireless Communications and Mobile Computing 2022 (August 17, 2022): 1–10. http://dx.doi.org/10.1155/2022/9392648.

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Aiming at the shortcomings of traditional bilateral filtering in suppressing speckle noise in SAR ship images, especially strong speckle noise and loss of image edge details, it proposes an improved bilateral filtering algorithm based on fast adaptive threshold and variable window in this paper. The algorithm was used to suppress speckle noise in SAR ship images. The traditional bilateral filtering cannot effectively filter out the strong speckle noise, but the SAR image has strong speckle noise because of the defects of its imaging principle. To solve these problems, an image sample truncatio

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Ma, Xiaoshuang, Le Li, and Gang Wang. "Blind Edge-Retention Indicator for Assessing the Quality of Filtered (Pol)SAR Images Based on a Ratio Gradient Operator and Confidence Interval Estimation." Remote Sensing 16, no. 11 (2024): 1992. http://dx.doi.org/10.3390/rs16111992.

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Speckle reduction is a key preprocessing approach for the applications of Synthetic Aperture Radar (SAR) data. For many interpretation tasks, high-quality SAR images with a rich texture and structure information are useful. Therefore, a satisfactory SAR image filter should retain this information well after processing. Some quantitative assessment indicators have been presented to evaluate the edge-preservation capability of single-polarization SAR filters, among which the non-clean-reference-based (i.e., blind) ones are attractive. However, most of these indicators are derived based only on t

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Zhang, Guo, Fengcheng Guo, Qingjun Zhang, Kai Xu, Peng Jia, and Xiaoyun Hao. "Speckle Reduction by Directional Coherent Anisotropic Diffusion." Remote Sensing 11, no. 23 (2019): 2768. http://dx.doi.org/10.3390/rs11232768.

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To effectively balance speckle smoothing and preservation of edges and radiation, a novel anisotropic diffusion filter was developed that uses a directional coherent coefficient. The proposed filter effectively improves the edge detection operator of a traditional anisotropic diffusion filter. The new edge detection operator calculates 16 direction coherence coefficients to avoid the interference of the edge direction. For the diffusion function, the proposed method directly uses the detected directional coherent edge as the diffusion coefficient, which simplifies the calculation of the diffus

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Gallegos-Funes, F., J. Martínez-Valdés, R. Cruz-Santiago, and J. López-Bonilla. "Wavelet Order Statistics Filters for Image Denoising." Journal of Scientific Research 1, no. 2 (2009): 248–57. http://dx.doi.org/10.3329/jsr.v1i2.2311.

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This paper presents the wavelet order statistics filters for the removal of impulsive and speckle noise in color image applications. The proposed filtering scheme is defined as two filters in the wavelet domain to conform to the structure of a general filter that can be modified in some headings. The first filter is based on redundancy of approaches and the second one is the wavelet domain iterative center weighted median algorithm. With the structure of the proposed filter different implementations for the estimation of the noisy sample are carried out using different order statistics algorit

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