{"title":"基于小波变换和维纳滤波的SAR图像去噪","authors":"Priyanka S. Tondewad, M. Dale","doi":"10.1109/ESCI56872.2023.10100330","DOIUrl":null,"url":null,"abstract":"Noise is unwanted signal present in the image. Speckle noise is usually present in Synthetic Aperture Radar (SAR), ultrasound or any active radar sensor images. This noise limits the information interpretation. The proposed novel method is realized by first applying frequency domain methods for high frequency noise removal and then applying spatial domain filters. We have demonstrated various transform-based methods. Frequency domain methods gives ease to use separate bands for processing. Stationary Wavelet transform based method proves to be more efficient. Visual quality is improved as compared to the traditional speckle noise removal filters also the qualitative parameters like Peak Signal-to-Noise Ratio (PSNR), Equivalent Number of Looks (ENL), Similarity Index Measure (SSIM) and Speckle Suppression Index (SSI) and Structural are improved.","PeriodicalId":441215,"journal":{"name":"2023 International Conference on Emerging Smart Computing and Informatics (ESCI)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Denoising of SAR Images using Wavelet Transforms and Wiener Filter\",\"authors\":\"Priyanka S. Tondewad, M. Dale\",\"doi\":\"10.1109/ESCI56872.2023.10100330\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Noise is unwanted signal present in the image. Speckle noise is usually present in Synthetic Aperture Radar (SAR), ultrasound or any active radar sensor images. This noise limits the information interpretation. The proposed novel method is realized by first applying frequency domain methods for high frequency noise removal and then applying spatial domain filters. We have demonstrated various transform-based methods. Frequency domain methods gives ease to use separate bands for processing. Stationary Wavelet transform based method proves to be more efficient. Visual quality is improved as compared to the traditional speckle noise removal filters also the qualitative parameters like Peak Signal-to-Noise Ratio (PSNR), Equivalent Number of Looks (ENL), Similarity Index Measure (SSIM) and Speckle Suppression Index (SSI) and Structural are improved.\",\"PeriodicalId\":441215,\"journal\":{\"name\":\"2023 International Conference on Emerging Smart Computing and Informatics (ESCI)\",\"volume\":\"18 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 International Conference on Emerging Smart Computing and Informatics (ESCI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ESCI56872.2023.10100330\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 International Conference on Emerging Smart Computing and Informatics (ESCI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ESCI56872.2023.10100330","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Denoising of SAR Images using Wavelet Transforms and Wiener Filter
Noise is unwanted signal present in the image. Speckle noise is usually present in Synthetic Aperture Radar (SAR), ultrasound or any active radar sensor images. This noise limits the information interpretation. The proposed novel method is realized by first applying frequency domain methods for high frequency noise removal and then applying spatial domain filters. We have demonstrated various transform-based methods. Frequency domain methods gives ease to use separate bands for processing. Stationary Wavelet transform based method proves to be more efficient. Visual quality is improved as compared to the traditional speckle noise removal filters also the qualitative parameters like Peak Signal-to-Noise Ratio (PSNR), Equivalent Number of Looks (ENL), Similarity Index Measure (SSIM) and Speckle Suppression Index (SSI) and Structural are improved.