{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,17]],"date-time":"2025-12-17T12:57:47Z","timestamp":1765976267116,"version":"build-2065373602"},"reference-count":60,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2019,2,13]],"date-time":"2019-02-13T00:00:00Z","timestamp":1550016000000},"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>The    M    estimator is a recently proposed image-quality index used to evaluate the despeckling operation in SAR (Synthetic Aperture Radar) data. It is used also to rank despeckling filters and to improve their design. As a difference with traditional image-quality estimators, it operates not on the filtered result but on a derived one, i.e., the ratio image. However, a deep statistical analysis of its properties remains open and, with it, the ability to use it as a test statistic. In this work, we focus on obtaining insights into its distribution as well as on exploring other remarkable statistical properties of this unassisted estimator. This study is performed through EDA (Exploratory Data Analysis) and the well-known ANOVA (ANalysis Of VAriance). We test our results on a set of simulated SAR data and provide guides to enrich the    M    estimator to extend its capabilities.<\/jats:p>","DOI":"10.3390\/rs11040385","type":"journal-article","created":{"date-parts":[[2019,2,14]],"date-time":"2019-02-14T03:21:46Z","timestamp":1550114506000},"page":"385","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Statistical Properties of an Unassisted Image Quality Index for SAR Imagery"],"prefix":"10.3390","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0667-2302","authenticated-orcid":false,"given":"Luis","family":"Gomez","sequence":"first","affiliation":[{"name":"CTIM\u2014Centro de Tecnolog\u00edas de la Imagen, University of Las Palmas de Gran Canaria, 35017 Las Palmas, Gran Canaria, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9884-9090","authenticated-orcid":false,"given":"Raydonal","family":"Ospina","sequence":"additional","affiliation":[{"name":"Departamento de Estat\u00edstica, CAST\u2014Computational Agriculture Statistics Laboratory, Universidade Federal de Pernambuco, Recife 50740-540, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8002-5341","authenticated-orcid":false,"given":"Alejandro C.","family":"Frery","sequence":"additional","affiliation":[{"name":"LaCCAN\u2014Laborat\u00f3rio de Computa\u00e7\u00e3o Cient\u00edfica e An\u00e1lise Num\u00e9rica, Universidade Federal de Alagoas, Macei\u00f3 AL 57072-900, Brazil"}]}],"member":"1968","published-online":{"date-parts":[[2019,2,13]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"6","DOI":"10.1109\/MGRS.2013.2248301","article-title":"A Tutorial on Synthetic Aperture Radar","volume":"1","author":"Moreira","year":"2013","journal-title":"IEEE Geosci. 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