{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,18]],"date-time":"2026-01-18T22:59:41Z","timestamp":1768777181195,"version":"3.49.0"},"reference-count":31,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2018,5,8]],"date-time":"2018-05-08T00:00:00Z","timestamp":1525737600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>To better reduce image speckle noise while also maintaining edge information in synthetic aperture radar (SAR) images, we propose a novel anisotropic diffusion algorithm using weighted Euclidean distance (WEDAD). Presented here is a modified speckle reducing anisotropic diffusion (SRAD) method, which constructs a new edge detection operator using weighted Euclidean distances. The new edge detection operator can adaptively distinguish between homogenous and heterogeneous image regions, effectively generate anisotropic diffusion coefficients for each image pixel, and filter each pixel at different scales. Additionally, the effects of two different weighting methods (Gaussian weighting and non-linear weighting) of de-noising were analyzed. The effect of different adjustment coefficient settings on speckle suppression was also explored. A series of experiments were conducted using an added noise image, GF-3 SAR image, and YG-29 SAR image. The experimental results demonstrate that the proposed method can not only significantly suppress speckle, thus improving the visual effects, but also better preserve the edge information of images.<\/jats:p>","DOI":"10.3390\/rs10050722","type":"journal-article","created":{"date-parts":[[2018,5,8]],"date-time":"2018-05-08T02:48:08Z","timestamp":1525747688000},"page":"722","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":22,"title":["Speckle Suppression by Weighted Euclidean Distance Anisotropic Diffusion"],"prefix":"10.3390","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4547-5507","authenticated-orcid":false,"given":"Fengcheng","family":"Guo","sequence":"first","affiliation":[{"name":"State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3987-5336","authenticated-orcid":false,"given":"Guo","family":"Zhang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China"},{"name":"Collaborative Innovation Center of Geospatial Technology, Wuhan University, Wuhan 430079, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5285-5738","authenticated-orcid":false,"given":"Qingjun","family":"Zhang","sequence":"additional","affiliation":[{"name":"Collaborative Innovation Center of Geospatial Technology, Wuhan University, Wuhan 430079, China"},{"name":"China Academy of Space Technology, Beijing 100094, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5416-7226","authenticated-orcid":false,"given":"Ruishan","family":"Zhao","sequence":"additional","affiliation":[{"name":"School of Geomatics, Liaoning Technical University, Fuxin 123000, China"}]},{"given":"Mingjun","family":"Deng","sequence":"additional","affiliation":[{"name":"School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6310-2977","authenticated-orcid":false,"given":"Kai","family":"Xu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China"}]}],"member":"1968","published-online":{"date-parts":[[2018,5,8]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"2196","DOI":"10.1109\/TGRS.2002.802473","article-title":"SAR speckle reduction using wavelet denoising and Markov random field modeling","volume":"40","author":"Xie","year":"2002","journal-title":"IEEE Trans. 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