{"title":"利用方差场扩散的小波域图像收缩","authors":"Zhenyu Liu, Jing Tian, Li Chen, Yongtao Wang","doi":"10.1109/ACPR.2011.6166660","DOIUrl":null,"url":null,"abstract":"Wavelet shrinkage is an image denoising technique based on the concept of thresholding the wavelet coefficients. The key challenge of wavelet shrinkage is to find an appropriate threshold value, which is typically controlled by the signal variance. To tackle this challenge, a new image shrinkage approach is proposed in this paper by using a variance field diffusion, which can provide more accurate variance estimation. Experimental results are provided to demonstrate the superior performance of the proposed approach.","PeriodicalId":287232,"journal":{"name":"The First Asian Conference on Pattern Recognition","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Wavelet-domain image shrinkage using variance field diffusion\",\"authors\":\"Zhenyu Liu, Jing Tian, Li Chen, Yongtao Wang\",\"doi\":\"10.1109/ACPR.2011.6166660\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Wavelet shrinkage is an image denoising technique based on the concept of thresholding the wavelet coefficients. The key challenge of wavelet shrinkage is to find an appropriate threshold value, which is typically controlled by the signal variance. To tackle this challenge, a new image shrinkage approach is proposed in this paper by using a variance field diffusion, which can provide more accurate variance estimation. Experimental results are provided to demonstrate the superior performance of the proposed approach.\",\"PeriodicalId\":287232,\"journal\":{\"name\":\"The First Asian Conference on Pattern Recognition\",\"volume\":\"14 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"The First Asian Conference on Pattern Recognition\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ACPR.2011.6166660\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"The First Asian Conference on Pattern Recognition","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ACPR.2011.6166660","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Wavelet-domain image shrinkage using variance field diffusion
Wavelet shrinkage is an image denoising technique based on the concept of thresholding the wavelet coefficients. The key challenge of wavelet shrinkage is to find an appropriate threshold value, which is typically controlled by the signal variance. To tackle this challenge, a new image shrinkage approach is proposed in this paper by using a variance field diffusion, which can provide more accurate variance estimation. Experimental results are provided to demonstrate the superior performance of the proposed approach.