Aram Danielyan, M. Vehvilainen, A. Foi, V. Katkovnik, K. Egiazarian
{"title":"杂讯原始数据的跨色BM3D滤波","authors":"Aram Danielyan, M. Vehvilainen, A. Foi, V. Katkovnik, K. Egiazarian","doi":"10.1109/LNLA.2009.5278395","DOIUrl":null,"url":null,"abstract":"Color image reconstruction from noisy color filter array (CFA) data is considered. A modification of the Block Matching 3D (BM3D) [2] filter for CFA data denoising utilizing cross-color correlations is proposed. Denoised images are then demosaicked by algorithms developed for noise-free data leading to state-of-the-art performance for both Gaussian and Poissonian noise models.","PeriodicalId":231766,"journal":{"name":"2009 International Workshop on Local and Non-Local Approximation in Image Processing","volume":"69 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"51","resultStr":"{\"title\":\"Cross-color BM3D filtering of noisy raw data\",\"authors\":\"Aram Danielyan, M. Vehvilainen, A. Foi, V. Katkovnik, K. Egiazarian\",\"doi\":\"10.1109/LNLA.2009.5278395\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Color image reconstruction from noisy color filter array (CFA) data is considered. A modification of the Block Matching 3D (BM3D) [2] filter for CFA data denoising utilizing cross-color correlations is proposed. Denoised images are then demosaicked by algorithms developed for noise-free data leading to state-of-the-art performance for both Gaussian and Poissonian noise models.\",\"PeriodicalId\":231766,\"journal\":{\"name\":\"2009 International Workshop on Local and Non-Local Approximation in Image Processing\",\"volume\":\"69 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-10-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"51\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 International Workshop on Local and Non-Local Approximation in Image Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/LNLA.2009.5278395\",\"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 Workshop on Local and Non-Local Approximation in Image Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/LNLA.2009.5278395","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Color image reconstruction from noisy color filter array (CFA) data is considered. A modification of the Block Matching 3D (BM3D) [2] filter for CFA data denoising utilizing cross-color correlations is proposed. Denoised images are then demosaicked by algorithms developed for noise-free data leading to state-of-the-art performance for both Gaussian and Poissonian noise models.