{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,23]],"date-time":"2026-07-23T15:33:32Z","timestamp":1784820812335,"version":"3.55.0"},"reference-count":49,"publisher":"MDPI AG","issue":"15","license":[{"start":{"date-parts":[[2022,7,27]],"date-time":"2022-07-27T00:00:00Z","timestamp":1658880000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61801419"],"award-info":[{"award-number":["61801419"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["2019FD114"],"award-info":[{"award-number":["2019FD114"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["202201AT070027"],"award-info":[{"award-number":["202201AT070027"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100005273","name":"Natural Science Foundation of Yunnan Province","doi-asserted-by":"publisher","award":["61801419"],"award-info":[{"award-number":["61801419"]}],"id":[{"id":"10.13039\/501100005273","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100005273","name":"Natural Science Foundation of Yunnan Province","doi-asserted-by":"publisher","award":["2019FD114"],"award-info":[{"award-number":["2019FD114"]}],"id":[{"id":"10.13039\/501100005273","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100005273","name":"Natural Science Foundation of Yunnan Province","doi-asserted-by":"publisher","award":["202201AT070027"],"award-info":[{"award-number":["202201AT070027"]}],"id":[{"id":"10.13039\/501100005273","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Synthetic aperture radar (SAR) image-change detection is widely used in various fields, such as environmental monitoring and ecological monitoring. There is too much noise and insufficient information utilization, which make the results of change detection inaccurate. Thus, we propose an SAR image-change-detection method based on multiplicative fusion difference image (DI), saliency detection (SD), multi-scale morphological reconstruction (MSMR), and fuzzy c-means (FCM) clustering. Firstly, a new fusion DI method is proposed by multiplying the ratio (R) method based on the ratio of the image before and after the change and the mean ratio (MR) method based on the ratio of the image neighborhood mean value. The new DI operator ratio\u2013mean ratio (RMR) enlarges the characteristics of unchanged areas and changed areas. Secondly, saliency detection is used in DI, which is conducive to the subsequent sub-area processing. Thirdly, we propose an improved FCM clustering-change-detection method based on MSMR. The proposed method has high computational efficiency, and the neighborhood information obtained by morphological reconstruction is fully used. Six real SAR data sets are used in different experiments to demonstrate the effectiveness of the proposed saliency ratio\u2013mean ratio with multi-scale morphological reconstruction fuzzy c-means (SRMR-MSMRFCM). Finally, four classical noise-sensitive methods are used to detect our DI method and demonstrate the strong denoising and detail-preserving ability.<\/jats:p>","DOI":"10.3390\/rs14153604","type":"journal-article","created":{"date-parts":[[2022,7,28]],"date-time":"2022-07-28T03:21:16Z","timestamp":1658978476000},"page":"3604","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Change Detection Based on Fusion Difference Image and Multi-Scale Morphological Reconstruction for SAR Images"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4094-2639","authenticated-orcid":false,"given":"Jiayu","family":"Xuan","sequence":"first","affiliation":[{"name":"School of Physics and Electronic Information Technology, Yunnan Normal University, Kunming 650500, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhihui","family":"Xin","sequence":"additional","affiliation":[{"name":"School of Physics and Electronic Information Technology, Yunnan Normal University, Kunming 650500, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guisheng","family":"Liao","sequence":"additional","affiliation":[{"name":"National Laboratory of Radar Signal Processing, Xidian University, Xi\u2019an 710071, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Penghui","family":"Huang","sequence":"additional","affiliation":[{"name":"School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhixu","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Physics and Electronic Information Technology, Yunnan Normal University, Kunming 650500, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yu","family":"Sun","sequence":"additional","affiliation":[{"name":"School of Physics and Electronic Information Technology, Yunnan Normal University, Kunming 650500, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,7,27]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"2365","DOI":"10.1080\/0143116031000139863","article-title":"Change detection techniques","volume":"25","author":"Lu","year":"2004","journal-title":"Int. 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