{"title":"从图像中去除盐和胡椒的光谱算法","authors":"Olivier Rioul","doi":"10.1109/DSPWS.1996.555514","DOIUrl":null,"url":null,"abstract":"This paper presents an elegant solution to the impulse noise cancellation problem for images. The approach taken here is based on the theory of error-correcting (BCH) codes. Impulses are considered as \"errors\". The process is in two steps: First, find the error locations in the image; then, correct the error values. A first pass is made on the lines of the image, a second pass is then performed on the columns. Next the same procedure is repeated. In most cases, impulse noise is completely removed after a few iterations are performed.","PeriodicalId":131323,"journal":{"name":"1996 IEEE Digital Signal Processing Workshop Proceedings","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1996-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"15","resultStr":"{\"title\":\"A spectral algorithm for removing salt and pepper from images\",\"authors\":\"Olivier Rioul\",\"doi\":\"10.1109/DSPWS.1996.555514\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents an elegant solution to the impulse noise cancellation problem for images. The approach taken here is based on the theory of error-correcting (BCH) codes. Impulses are considered as \\\"errors\\\". The process is in two steps: First, find the error locations in the image; then, correct the error values. A first pass is made on the lines of the image, a second pass is then performed on the columns. Next the same procedure is repeated. In most cases, impulse noise is completely removed after a few iterations are performed.\",\"PeriodicalId\":131323,\"journal\":{\"name\":\"1996 IEEE Digital Signal Processing Workshop Proceedings\",\"volume\":\"18 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1996-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"15\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"1996 IEEE Digital Signal Processing Workshop Proceedings\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/DSPWS.1996.555514\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"1996 IEEE Digital Signal Processing Workshop Proceedings","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DSPWS.1996.555514","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A spectral algorithm for removing salt and pepper from images
This paper presents an elegant solution to the impulse noise cancellation problem for images. The approach taken here is based on the theory of error-correcting (BCH) codes. Impulses are considered as "errors". The process is in two steps: First, find the error locations in the image; then, correct the error values. A first pass is made on the lines of the image, a second pass is then performed on the columns. Next the same procedure is repeated. In most cases, impulse noise is completely removed after a few iterations are performed.