Article(id=1242119398333420401, tenantId=1146029695717560320, journalId=1146031591421210625, issueId=1242119397003826032, articleNumber=null, orderNo=null, doi=null, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1259683200000, receivedDateStr=2009-12-02, revisedDate=1260979200000, revisedDateStr=2009-12-17, acceptedDate=null, acceptedDateStr=null, onlineDate=1263312000000, onlineDateStr=2010-01-13, pubDate=1263312000000, pubDateStr=2010-01-13, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1263312000000, onlineIssueDateStr=2010-01-13, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1774073942021, creator=sys-migrate, updateTime=1774073942021, updator=sys-migrate, issue=Issue{id=1242119397003826032, tenantId=1146029695717560320, journalId=1146031591421210625, year='2010', volume='28', issue='1001', pageStart='1', pageEnd='139', issueExtLink='null', onlineDate='null', pubDate='1263312000000', pubDateStr='2010-01-13', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=3, issueType=-1, specialIssue=null, createTime=1774073941703, creator='sys-migrate', updateTime=1774073941703, updator='sys-migrate', preIssue=null, nextIssue=null, articleTotal=null, ext=null, issueFiles=null, downloadFileDto=null}, startPage=102, endPage=106, ext={EN=ArticleExt(id=1242119401495921370, articleId=1242119398333420401, tenantId=1146029695717560320, journalId=1146031591421210625, language=EN, title=Wavelet Transform Used in Image Denoising, columnId=1242116810380743325, journalTitle=Science & Technology Review, columnName=Reviews, runingTitle=null, highlight=null, articleAbstract=This paper reviews studies of wavelet transform used in image denoising. Image denoising is an indispensable part in image processing, and plays an important role in the field of computer vision. As there is only a single scale in the frequency domain, only a general information can be extracted from the image. The multi-scale and multi-resolution features of wavelet domain make it possible for image denoising to be conducted at different scales. For a better understanding of image denoising, this paper first discusses briefly the mathematical model of image noise, the basic principles and the traditional methods used for image denoising and then, the image denoising theory based on wavelet transform. Three kinds of image denoising methods commonly used in wavelet demain are highlighted, as well as, the advantages and disadvantages of these methods. Finally, the recent development of the wavelet de-noising is reviewed., authors=null, authorsList=null, authorCompany=null, correspAuthors=null, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=8dHoKX7iiVQghzkToAiYlA==, pdfFileSize=401823, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1242119400812254076, articleId=1242119398333420401, tenantId=1146029695717560320, journalId=1146031591421210625, language=CN, title=小波变换在图像去噪中的应用, columnId=1242116809164390686, journalTitle=科技导报, columnName=综述文章, runingTitle=null, highlight=null, articleAbstract=图像小波域去噪可克服频域去噪单一尺度的局限性，具备多尺度多分辨率的特点，已成为目前图像去噪的主要方法之一。为归纳小波变换在图像去噪领域中的应用，简要讨论图像噪声的概念、数学模型、传统图像去噪的基本原理方法，详细阐述了图像小波域去噪的基本理论、发展过程、去噪方法，评价了3种常用方法的优缺点，对小波去噪的发展趋势进行了展望。, authors=艾泽潭,石庚辰, authorsList=艾泽潭;石庚辰, authorCompany=北京理工大学机电工程学院， 北京 100081, correspAuthors=null, authorNote=null, correspAuthorsNote=石庚辰, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=VadF1LA9fe47nv1fOADA5w==, pdfFileSize=401823, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null)}, authors=null, keywords=[Keyword(id=1242119400459932536, tenantId=1146029695717560320, journalId=1146031591421210625, articleId=1242119398333420401, language=CN, orderNo=1, keyword=小波变换), Keyword(id=1242119400552207226, tenantId=1146029695717560320, 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