{"title":"空域滤波器去除SAR图像散斑噪声的性能比较分析","authors":"Ranjith Kumar Painam, M. Suchetha","doi":"10.1109/ICEEICT53079.2022.9768585","DOIUrl":null,"url":null,"abstract":"In synthetic aperture radar (SAR) images, speckle noise is common, and SAR data is handled coherently. Multiplicative noise is another name for speckle. The purpose of this paper is to compare several approaches for reducing speckle noise. These techniques will be used to demonstrate trends and numerous different approaches that have evolved over the years. The technical aspects of the various adaptive spatial domain filters were discussed in this paper, and they were summarised for use in removing speckle noise from SAR images. ENL, SSI, and SSIM are the performance parameters that have been quantitatively and qualitatively analysed. It indicates that the adaptive filters with varied window sizes can be used to eliminate speckle and that noise suppression is more effective in SAR images. It may be enhanced to incorporate several machine learning techniques to optimise the result in order to improve various performance parameters. The experimental results show that the structural details are better preserved while speckle noise is suppressed.","PeriodicalId":201910,"journal":{"name":"2022 First International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Comparative Performance Analysis of Spatial Domain Filters for Removing Speckle Noise in SAR images\",\"authors\":\"Ranjith Kumar Painam, M. Suchetha\",\"doi\":\"10.1109/ICEEICT53079.2022.9768585\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In synthetic aperture radar (SAR) images, speckle noise is common, and SAR data is handled coherently. Multiplicative noise is another name for speckle. The purpose of this paper is to compare several approaches for reducing speckle noise. These techniques will be used to demonstrate trends and numerous different approaches that have evolved over the years. The technical aspects of the various adaptive spatial domain filters were discussed in this paper, and they were summarised for use in removing speckle noise from SAR images. ENL, SSI, and SSIM are the performance parameters that have been quantitatively and qualitatively analysed. It indicates that the adaptive filters with varied window sizes can be used to eliminate speckle and that noise suppression is more effective in SAR images. It may be enhanced to incorporate several machine learning techniques to optimise the result in order to improve various performance parameters. The experimental results show that the structural details are better preserved while speckle noise is suppressed.\",\"PeriodicalId\":201910,\"journal\":{\"name\":\"2022 First International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT)\",\"volume\":\"43 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-02-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 First International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICEEICT53079.2022.9768585\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 First International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICEEICT53079.2022.9768585","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Comparative Performance Analysis of Spatial Domain Filters for Removing Speckle Noise in SAR images
In synthetic aperture radar (SAR) images, speckle noise is common, and SAR data is handled coherently. Multiplicative noise is another name for speckle. The purpose of this paper is to compare several approaches for reducing speckle noise. These techniques will be used to demonstrate trends and numerous different approaches that have evolved over the years. The technical aspects of the various adaptive spatial domain filters were discussed in this paper, and they were summarised for use in removing speckle noise from SAR images. ENL, SSI, and SSIM are the performance parameters that have been quantitatively and qualitatively analysed. It indicates that the adaptive filters with varied window sizes can be used to eliminate speckle and that noise suppression is more effective in SAR images. It may be enhanced to incorporate several machine learning techniques to optimise the result in order to improve various performance parameters. The experimental results show that the structural details are better preserved while speckle noise is suppressed.