{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,17]],"date-time":"2026-01-17T09:36:08Z","timestamp":1768642568355,"version":"3.49.0"},"reference-count":31,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2016,10,10]],"date-time":"2016-10-10T00:00:00Z","timestamp":1476057600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Military and Civilian Highway Traffic Application Program of China","award":["GFZX0404080102"],"award-info":[{"award-number":["GFZX0404080102"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61401077"],"award-info":[{"award-number":["61401077"]}],"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":["61401428"],"award-info":[{"award-number":["61401428"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Hundred Talent Program of Chinese Academy of Sciences","award":["Y53Z180390"],"award-info":[{"award-number":["Y53Z180390"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>An interferometric synthetic aperture radar (InSAR) phase denoising algorithm using the local sparsity of wavelet coefficients and nonlocal similarity of grouped blocks was developed. From the Bayesian perspective, the double-    l 1     norm regularization model that enforces the local and nonlocal sparsity constraints was used. Taking advantages of coefficients of the nonlocal similarity between group blocks for the wavelet shrinkage, the proposed algorithm effectively filtered the phase noise. Applying the method to simulated and acquired InSAR data, we obtained satisfactory results. In comparison, the algorithm outperformed several widely-used InSAR phase denoising approaches in terms of the number of residues, root-mean-square errors and other edge preservation indexes.<\/jats:p>","DOI":"10.3390\/rs8100830","type":"journal-article","created":{"date-parts":[[2016,10,10]],"date-time":"2016-10-10T10:35:19Z","timestamp":1476095719000},"page":"830","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["A Sparsity-Based InSAR Phase Denoising Algorithm Using Nonlocal Wavelet Shrinkage"],"prefix":"10.3390","volume":"8","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4710-9575","authenticated-orcid":false,"given":"Dongsheng","family":"Fang","sequence":"first","affiliation":[{"name":"Key Laboratory of Technology in Geo-Spatial Information Processing and Application System, Institute of Electronics, Chinese Academy of Sciences, Beijing 100190, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100039, China"}]},{"given":"Xiaolei","family":"Lv","sequence":"additional","affiliation":[{"name":"Key Laboratory of Technology in Geo-Spatial Information Processing and Application System, Institute of Electronics, Chinese Academy of Sciences, Beijing 100190, China"}]},{"given":"Yong","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Geography, Planning and Environment, East Carolina University, Greenville, NC 27858, USA"}]},{"given":"Xue","family":"Lin","sequence":"additional","affiliation":[{"name":"School of Information Science and Engineering, University of Jinan, Jinan 250022, China"}]},{"given":"Jiang","family":"Qian","sequence":"additional","affiliation":[{"name":"School of Resources and Environment, University of Electronic Science and Technology of China, Chengdu 611731, China"}]}],"member":"1968","published-online":{"date-parts":[[2016,10,10]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Eichel, P.H., Ghiglia, D.C., and Jakowatz, C.V. 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