Janisson Batista de Jesus, Tatiana Mora Kuplich, Íkaro Daniel de Carvalho Barreto, Fernando Luis Hillebrand, Cristiano Niederauer da Rosa
{"title":"Speckle reduction for Sentinel-1A SAR images in the Semi-arid caatinga region, Brazil","authors":"Janisson Batista de Jesus, Tatiana Mora Kuplich, Íkaro Daniel de Carvalho Barreto, Fernando Luis Hillebrand, Cristiano Niederauer da Rosa","doi":"10.1590/s1982-21702023000300007","DOIUrl":null,"url":null,"abstract":"Due to the absence of studies related to the digital processing of synthetic aperture radar (SAR) images in the semi-arid region of Brazil, the aim of this study was to test different filters for reducing speckle noise in SAR images, serving as a reference for choosing the most suitable filter for different studies in this vegetation. The filters: Gamma Map, Lee Sigma, Median, Frost and Refined Lee in different window sizes were tested on the VV, VH and VH/VV polarizations in the Sentinel-1A images, verifying the responses under the influence of the dry and post-rainy period in the Caatinga vegetation. In the state of Sergipe, Brazil, 30 samples of Caatinga fragments obtained from Sentinel-1A images for the dry and post-rainy season were selected. For all images evaluated, the values of the averages of the equivalent number of looks (ENL) were compared by the Tukey test at 5% significance. The Gamma filter showed the highest amount of means (22) with the highest ENL values, followed by Median (5). The generation of ENL results and their comparison, considering all variables used, was essential to serve as a basis for choosing the filtering method in studies that use data from Sentinel-1A in the Caatinga region.","PeriodicalId":55347,"journal":{"name":"Boletim De Ciencias Geodesicas","volume":"38 1","pages":"0"},"PeriodicalIF":0.5000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Boletim De Ciencias Geodesicas","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1590/s1982-21702023000300007","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Earth and Planetary Sciences","Score":null,"Total":0}
引用次数: 0
Abstract
Due to the absence of studies related to the digital processing of synthetic aperture radar (SAR) images in the semi-arid region of Brazil, the aim of this study was to test different filters for reducing speckle noise in SAR images, serving as a reference for choosing the most suitable filter for different studies in this vegetation. The filters: Gamma Map, Lee Sigma, Median, Frost and Refined Lee in different window sizes were tested on the VV, VH and VH/VV polarizations in the Sentinel-1A images, verifying the responses under the influence of the dry and post-rainy period in the Caatinga vegetation. In the state of Sergipe, Brazil, 30 samples of Caatinga fragments obtained from Sentinel-1A images for the dry and post-rainy season were selected. For all images evaluated, the values of the averages of the equivalent number of looks (ENL) were compared by the Tukey test at 5% significance. The Gamma filter showed the highest amount of means (22) with the highest ENL values, followed by Median (5). The generation of ENL results and their comparison, considering all variables used, was essential to serve as a basis for choosing the filtering method in studies that use data from Sentinel-1A in the Caatinga region.
期刊介绍:
The Boletim de Ciências Geodésicas publishes original papers in the area of Geodetic Sciences and correlated ones (Geodesy, Photogrammetry and Remote Sensing, Cartography and Geographic Information Systems).
Submitted articles must be unpublished, and should not be under consideration for publication in any other journal. Previous publication of the paper in conference proceedings would not violate the originality requirements. Articles must be written preferably in English language.