{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,18]],"date-time":"2026-08-18T00:30:28Z","timestamp":1787013028742,"version":"3.56.0"},"reference-count":51,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Geosci. Remote Sensing"],"published-print":{"date-parts":[[2022]]},"DOI":"10.1109\/tgrs.2021.3128621","type":"journal-article","created":{"date-parts":[[2021,11,16]],"date-time":"2021-11-16T15:28:05Z","timestamp":1637076485000},"page":"1-13","source":"Crossref","is-referenced-by-count":97,"title":["As If by Magic: Self-Supervised Training of Deep Despeckling Networks With MERLIN"],"prefix":"10.1109","volume":"60","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7170-9015","authenticated-orcid":false,"given":"Emanuele","family":"Dalsasso","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9216-8318","authenticated-orcid":false,"given":"Loic","family":"Denis","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3110-8183","authenticated-orcid":false,"given":"Florence","family":"Tupin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1016\/0734-189X(83)90047-6"},{"key":"ref2","article-title":"Deep learning methods for synthetic aperture radar image despeckling: An overview of trends and perspectives","volume-title":"arXiv:2012.05508","author":"Fracastoro","year":"2020"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/MGRS.2020.3046356"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/IGARSS47720.2021.9555039"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2005.864142"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/36.62623"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1137\/060671814"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2009.2019302"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2010.2045029"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1007\/s10851-009-0179-5"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1007\/3-540-44935-3_21"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/JSTARS.2016.2555579"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2002.802473"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-02256-2_24"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1137\/040616024"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2007.901238"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2014.2311305"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/IGARSS.2019.8900596"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2009.2029593"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2011.2161586"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/LGRS.2013.2271650"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2010.2076376"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2010.2087763"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2013.04.001"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2014.2352555"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/LSP.2017.2758203"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/CAMSAP.2017.8313133"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.3390\/rs10020196"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.3390\/rs11131532"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.3390\/rs12162636"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2013.2246838"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/JSTARS.2018.2790987"},{"key":"ref33","first-page":"1233","article-title":"How to handle spatial correlations in SAR despeckling? Resampling strategies and deep learning approaches","volume-title":"Proc. 13th Eur. Conf. Synth. Aperture Radar (EUSAR)","author":"Dalsasso"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/IGARSS.2017.8128234"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.3390\/rs12061006"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/JSTARS.2021.3071864"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/IGARSS39084.2020.9324183"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2021.3065461"},{"key":"ref39","first-page":"6970","article-title":"High-quality self-supervised deep image denoising","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Laine"},{"key":"ref40","article-title":"Noise2Kernel: Adaptive self-supervised blind denoising using a dilated convolutional kernel architecture","volume-title":"arXiv:2012.03623","author":"Lee","year":"2020"},{"key":"ref41","article-title":"Noise2Same: Optimizing a self-supervised bound for image denoising","volume-title":"arXiv:2010.11971","author":"Xie","year":"2020"},{"key":"ref42","first-page":"2965","article-title":"Noise2Noise: Learning image restoration without clean data","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Lehtinen"},{"key":"ref43","volume-title":"Speckle Phenomena in Optics: Theory and Applications","author":"Goodman","year":"2007"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"ref45","article-title":"Why gradient clipping accelerates training: A theoretical justification for adaptivity","volume-title":"arXiv:1905.11881","author":"Zhang","year":"2019"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.23919\/EURAD.2017.8249179"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1049\/SBRA509E_ch8"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/JSTARS.2017.2747118"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/LGRS.2019.2957240"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/MGRS.2020.3004508"},{"issue":"1","key":"ref51","article-title":"Definition of the TOPS SLC deramping function for products generated by the S-1 IPF","author":"Miranda","year":"2014"}],"container-title":["IEEE Transactions on Geoscience and Remote Sensing"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/36\/9633014\/09617648.pdf?arnumber=9617648","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,11]],"date-time":"2024-01-11T19:40:48Z","timestamp":1705002048000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9617648\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"references-count":51,"URL":"https:\/\/doi.org\/10.1109\/tgrs.2021.3128621","relation":{},"ISSN":["0196-2892","1558-0644"],"issn-type":[{"value":"0196-2892","type":"print"},{"value":"1558-0644","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022]]}}}