{"title":"基于二阶差分检测和方向加权中值滤波去除随机值脉冲噪声","authors":"P. K. Sa, Ratnakar Dash, B. Majhi","doi":"10.1109/ICIINFS.2009.5429836","DOIUrl":null,"url":null,"abstract":"The proposed approach of removal of random valued impulsive noise from images works in two phases. The first phase detects contaminated pixels and the second phase filters only those pixels keeping others intact. The detection scheme utilizes second order difference of pixels in a test window and the filtering scheme is a variation median filter based on the edge information. The proposed scheme is simulated extensively on standard images and comparison with existing schemes reveal that our scheme outperforms them in terms of Peak Signal to Noise Ratio (PSNR), number of false detection and miss detection. The proposed scheme is also good at preserving finer details. Further, the computational complexity and number of iterations needed by the proposed scheme is less than the existing counterparts.","PeriodicalId":117199,"journal":{"name":"2009 International Conference on Industrial and Information Systems (ICIIS)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"33","resultStr":"{\"title\":\"Second order difference based detection and directional weighted median filter for removal of random valued impulsive noise\",\"authors\":\"P. K. Sa, Ratnakar Dash, B. Majhi\",\"doi\":\"10.1109/ICIINFS.2009.5429836\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The proposed approach of removal of random valued impulsive noise from images works in two phases. The first phase detects contaminated pixels and the second phase filters only those pixels keeping others intact. The detection scheme utilizes second order difference of pixels in a test window and the filtering scheme is a variation median filter based on the edge information. The proposed scheme is simulated extensively on standard images and comparison with existing schemes reveal that our scheme outperforms them in terms of Peak Signal to Noise Ratio (PSNR), number of false detection and miss detection. The proposed scheme is also good at preserving finer details. Further, the computational complexity and number of iterations needed by the proposed scheme is less than the existing counterparts.\",\"PeriodicalId\":117199,\"journal\":{\"name\":\"2009 International Conference on Industrial and Information Systems (ICIIS)\",\"volume\":\"53 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"33\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 International Conference on Industrial and Information Systems (ICIIS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICIINFS.2009.5429836\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 International Conference on Industrial and Information Systems (ICIIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIINFS.2009.5429836","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Second order difference based detection and directional weighted median filter for removal of random valued impulsive noise
The proposed approach of removal of random valued impulsive noise from images works in two phases. The first phase detects contaminated pixels and the second phase filters only those pixels keeping others intact. The detection scheme utilizes second order difference of pixels in a test window and the filtering scheme is a variation median filter based on the edge information. The proposed scheme is simulated extensively on standard images and comparison with existing schemes reveal that our scheme outperforms them in terms of Peak Signal to Noise Ratio (PSNR), number of false detection and miss detection. The proposed scheme is also good at preserving finer details. Further, the computational complexity and number of iterations needed by the proposed scheme is less than the existing counterparts.