{"title":"Image denoising algorithm based on hybrid neighborhood filter","authors":"S. Hussain, Sami M. Gorashi","doi":"10.1109/ICSIPA.2013.6707972","DOIUrl":null,"url":null,"abstract":"Image denoising is an active area of research and probably one of the most studied problems in the image processing fields. In this paper we describe a new hybrid image denoising algorithm which combines Gaussian based neighborhood spatial filter with wavelet transform that based on neighborhood thresholding function which takes the correlation of the magnitude of the wavelet coefficient with its neighbors into consideration to decide whether the coefficient is noisy or noise free. Accordingly, noises are detected with the help of the surrounding information and are removed. Experimental results show that the proposed algorithm can effectively remove the image noises with less processing time as compared with the state-of-the-art denoising algorithm.","PeriodicalId":440373,"journal":{"name":"2013 IEEE International Conference on Signal and Image Processing Applications","volume":"65 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE International Conference on Signal and Image Processing Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSIPA.2013.6707972","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
Image denoising is an active area of research and probably one of the most studied problems in the image processing fields. In this paper we describe a new hybrid image denoising algorithm which combines Gaussian based neighborhood spatial filter with wavelet transform that based on neighborhood thresholding function which takes the correlation of the magnitude of the wavelet coefficient with its neighbors into consideration to decide whether the coefficient is noisy or noise free. Accordingly, noises are detected with the help of the surrounding information and are removed. Experimental results show that the proposed algorithm can effectively remove the image noises with less processing time as compared with the state-of-the-art denoising algorithm.