{"title":"基于稀疏先验的非局部聚类运动图像去噪","authors":"Ying Zhang","doi":"10.4108/eai.13-1-2022.172817","DOIUrl":null,"url":null,"abstract":"Image denoising is very important in image preprocessing. In order to introduce the priori information of external clean image into the denoising process, a non-local clustering image denoising algorithm is proposed. A sparse representation dictionary is obtained by combining the image blocks of external clean image and internal noise image. The sparse coefficient estimation of ideal image is obtained by global similar block matching. Based on the class dictionary and the estimated sparse coefficient, a sparse reconstruction method based on compressed sensing technology is used to denoise the image. Experimental results show that compared with traditional image denoising methods, the proposed algorithm can significantly reduce the denoising block effect and preserve more details while transitioning more naturally in the flat area of the image.","PeriodicalId":43034,"journal":{"name":"EAI Endorsed Transactions on Scalable Information Systems","volume":"25 1","pages":"14"},"PeriodicalIF":1.1000,"publicationDate":"2022-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Non-local clustering via sparse prior for sports image denoising\",\"authors\":\"Ying Zhang\",\"doi\":\"10.4108/eai.13-1-2022.172817\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Image denoising is very important in image preprocessing. In order to introduce the priori information of external clean image into the denoising process, a non-local clustering image denoising algorithm is proposed. A sparse representation dictionary is obtained by combining the image blocks of external clean image and internal noise image. The sparse coefficient estimation of ideal image is obtained by global similar block matching. Based on the class dictionary and the estimated sparse coefficient, a sparse reconstruction method based on compressed sensing technology is used to denoise the image. Experimental results show that compared with traditional image denoising methods, the proposed algorithm can significantly reduce the denoising block effect and preserve more details while transitioning more naturally in the flat area of the image.\",\"PeriodicalId\":43034,\"journal\":{\"name\":\"EAI Endorsed Transactions on Scalable Information Systems\",\"volume\":\"25 1\",\"pages\":\"14\"},\"PeriodicalIF\":1.1000,\"publicationDate\":\"2022-01-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"EAI Endorsed Transactions on Scalable Information Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4108/eai.13-1-2022.172817\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"COMPUTER SCIENCE, INFORMATION SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"EAI Endorsed Transactions on Scalable Information Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4108/eai.13-1-2022.172817","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
Non-local clustering via sparse prior for sports image denoising
Image denoising is very important in image preprocessing. In order to introduce the priori information of external clean image into the denoising process, a non-local clustering image denoising algorithm is proposed. A sparse representation dictionary is obtained by combining the image blocks of external clean image and internal noise image. The sparse coefficient estimation of ideal image is obtained by global similar block matching. Based on the class dictionary and the estimated sparse coefficient, a sparse reconstruction method based on compressed sensing technology is used to denoise the image. Experimental results show that compared with traditional image denoising methods, the proposed algorithm can significantly reduce the denoising block effect and preserve more details while transitioning more naturally in the flat area of the image.