{"title":"一种新的非局部均值图像去噪方法","authors":"Zheng Haozhe, Jin Yunan, Lu Xiaomei","doi":"10.1109/ICINIS.2010.24","DOIUrl":null,"url":null,"abstract":"An improve method of the block wise non-local means (BNL - means) is proposed for removing noise in the digital image. This method consists of the spectral decomposition of the Gaussian weighted matrix, the pseudo filter constructions, computations of the pseudo weighted coefficients and image denoising using the weighted sum of Gaussian. Experimental results show that this method is simpler, more efficient than the traditional NL-means algorithm and the denoising results are promising for the natural and textural image over the additive Gaussian white noise.","PeriodicalId":319379,"journal":{"name":"2010 Third International Conference on Intelligent Networks and Intelligent Systems","volume":"50 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Novel Non-local Means Method for Image Denoising\",\"authors\":\"Zheng Haozhe, Jin Yunan, Lu Xiaomei\",\"doi\":\"10.1109/ICINIS.2010.24\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An improve method of the block wise non-local means (BNL - means) is proposed for removing noise in the digital image. This method consists of the spectral decomposition of the Gaussian weighted matrix, the pseudo filter constructions, computations of the pseudo weighted coefficients and image denoising using the weighted sum of Gaussian. Experimental results show that this method is simpler, more efficient than the traditional NL-means algorithm and the denoising results are promising for the natural and textural image over the additive Gaussian white noise.\",\"PeriodicalId\":319379,\"journal\":{\"name\":\"2010 Third International Conference on Intelligent Networks and Intelligent Systems\",\"volume\":\"50 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 Third International Conference on Intelligent Networks and Intelligent Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICINIS.2010.24\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 Third International Conference on Intelligent Networks and Intelligent Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICINIS.2010.24","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An improve method of the block wise non-local means (BNL - means) is proposed for removing noise in the digital image. This method consists of the spectral decomposition of the Gaussian weighted matrix, the pseudo filter constructions, computations of the pseudo weighted coefficients and image denoising using the weighted sum of Gaussian. Experimental results show that this method is simpler, more efficient than the traditional NL-means algorithm and the denoising results are promising for the natural and textural image over the additive Gaussian white noise.