{"title":"一种基于形态学的偏振图像斑点去除新方法","authors":"Akhil Masurkar, R. Daruwala, V. Turkar","doi":"10.1109/InGARSS48198.2020.9358974","DOIUrl":null,"url":null,"abstract":"The most commonly present noise in Polarimetric Synthetic Aperture Radar (POLSAR) images is the Speckle Noise. This paper focuses on the removal of Speckle from SAR images using morphological operations like opening and closing which are based on the principles of erosion and dilation. A quantitative analysis of the image quality after processing with morphological operations is carried out using the most used, full reference and no reference quality metrics. The full reference quality metrics considered are Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR) and Structural Similarity Index (SSIM). The no reference quality metrics considered are Blind/Reference less Image Spatial Quality Evaluator (BRISQUE), Natural Image Quality Evaluator (NIQE), and Perception based Image Quality Evaluator (PIQE). The technique is focused around preserving point targets while removing noise. The results of proposed filters are compared with the existing filters. It is observed that the proposed technique can reduce the speckle significantly.","PeriodicalId":6797,"journal":{"name":"2020 IEEE India Geoscience and Remote Sensing Symposium (InGARSS)","volume":"514 1","pages":"126-129"},"PeriodicalIF":0.0000,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Novel Method to Remove Speckle from Polsar Images using Morphological Operations\",\"authors\":\"Akhil Masurkar, R. Daruwala, V. Turkar\",\"doi\":\"10.1109/InGARSS48198.2020.9358974\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The most commonly present noise in Polarimetric Synthetic Aperture Radar (POLSAR) images is the Speckle Noise. This paper focuses on the removal of Speckle from SAR images using morphological operations like opening and closing which are based on the principles of erosion and dilation. A quantitative analysis of the image quality after processing with morphological operations is carried out using the most used, full reference and no reference quality metrics. The full reference quality metrics considered are Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR) and Structural Similarity Index (SSIM). The no reference quality metrics considered are Blind/Reference less Image Spatial Quality Evaluator (BRISQUE), Natural Image Quality Evaluator (NIQE), and Perception based Image Quality Evaluator (PIQE). The technique is focused around preserving point targets while removing noise. The results of proposed filters are compared with the existing filters. It is observed that the proposed technique can reduce the speckle significantly.\",\"PeriodicalId\":6797,\"journal\":{\"name\":\"2020 IEEE India Geoscience and Remote Sensing Symposium (InGARSS)\",\"volume\":\"514 1\",\"pages\":\"126-129\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE India Geoscience and Remote Sensing Symposium (InGARSS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/InGARSS48198.2020.9358974\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE India Geoscience and Remote Sensing Symposium (InGARSS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/InGARSS48198.2020.9358974","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Novel Method to Remove Speckle from Polsar Images using Morphological Operations
The most commonly present noise in Polarimetric Synthetic Aperture Radar (POLSAR) images is the Speckle Noise. This paper focuses on the removal of Speckle from SAR images using morphological operations like opening and closing which are based on the principles of erosion and dilation. A quantitative analysis of the image quality after processing with morphological operations is carried out using the most used, full reference and no reference quality metrics. The full reference quality metrics considered are Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR) and Structural Similarity Index (SSIM). The no reference quality metrics considered are Blind/Reference less Image Spatial Quality Evaluator (BRISQUE), Natural Image Quality Evaluator (NIQE), and Perception based Image Quality Evaluator (PIQE). The technique is focused around preserving point targets while removing noise. The results of proposed filters are compared with the existing filters. It is observed that the proposed technique can reduce the speckle significantly.