{"title":"The de-noising method of threshold function based on wavelet","authors":"Kun Yang, Caixia Deng, Yu Chen, Li-Xiang Xu","doi":"10.1109/ICWAPR.2014.6961296","DOIUrl":null,"url":null,"abstract":"Image in the process of collection and storage can produce noise. Wavelet threshold de-noising is a method to remove noise effectively. The threshold function is a key in wavelet threshold de-noising method. In view of the hard-threshold function discontinuity and soft-threshold function deviation problem, through the analysis of the existing wavelet threshold de-noising methods, we present the improvement de-noising method of threshold function with the parameters in adjustable. Through experiments, we compare our method with the existing methods of wavelet threshold de-noising. In terms of the evaluation criteria, we find that the improved method of threshold function can remove the noise effectively.","PeriodicalId":439086,"journal":{"name":"2014 International Conference on Wavelet Analysis and Pattern Recognition","volume":"63 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 International Conference on Wavelet Analysis and Pattern Recognition","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICWAPR.2014.6961296","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7
Abstract
Image in the process of collection and storage can produce noise. Wavelet threshold de-noising is a method to remove noise effectively. The threshold function is a key in wavelet threshold de-noising method. In view of the hard-threshold function discontinuity and soft-threshold function deviation problem, through the analysis of the existing wavelet threshold de-noising methods, we present the improvement de-noising method of threshold function with the parameters in adjustable. Through experiments, we compare our method with the existing methods of wavelet threshold de-noising. In terms of the evaluation criteria, we find that the improved method of threshold function can remove the noise effectively.