{"title":"基于尺度间相关的非抽取小波收缩图像去噪算法","authors":"V. Vidya","doi":"10.1109/FGCNS.2008.19","DOIUrl":null,"url":null,"abstract":"This paper presents an image denoising scheme based on the correlation of the wavelet coefficients. It is well settled that significant features in images evolve with high magnitude across wavelet scales, while noise decays rapidly. Multiplying the adjacent wavelet scales sharpens the edges structures while weakening noise. This property is exploited by applying threshold to the scale correlation to identify the important features. Non-decimated wavelet transform is used here. Experiments shows that proposed method gives better results compared to other related works.","PeriodicalId":370780,"journal":{"name":"2008 Second International Conference on Future Generation Communication and Networking Symposia","volume":"28 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Non-Decimated Wavelet Shrinkage Algorithm for Image Denoising Based on Inter-Scale Correlation\",\"authors\":\"V. Vidya\",\"doi\":\"10.1109/FGCNS.2008.19\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents an image denoising scheme based on the correlation of the wavelet coefficients. It is well settled that significant features in images evolve with high magnitude across wavelet scales, while noise decays rapidly. Multiplying the adjacent wavelet scales sharpens the edges structures while weakening noise. This property is exploited by applying threshold to the scale correlation to identify the important features. Non-decimated wavelet transform is used here. Experiments shows that proposed method gives better results compared to other related works.\",\"PeriodicalId\":370780,\"journal\":{\"name\":\"2008 Second International Conference on Future Generation Communication and Networking Symposia\",\"volume\":\"28 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-12-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 Second International Conference on Future Generation Communication and Networking Symposia\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/FGCNS.2008.19\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 Second International Conference on Future Generation Communication and Networking Symposia","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/FGCNS.2008.19","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Non-Decimated Wavelet Shrinkage Algorithm for Image Denoising Based on Inter-Scale Correlation
This paper presents an image denoising scheme based on the correlation of the wavelet coefficients. It is well settled that significant features in images evolve with high magnitude across wavelet scales, while noise decays rapidly. Multiplying the adjacent wavelet scales sharpens the edges structures while weakening noise. This property is exploited by applying threshold to the scale correlation to identify the important features. Non-decimated wavelet transform is used here. Experiments shows that proposed method gives better results compared to other related works.