Article(id=1242117260031099544, tenantId=1146029695717560320, journalId=1146031591421210625, issueId=1242117211490419171, 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=-2209017600000, receivedDateStr=1900-01-01, revisedDate=-2209017600000, revisedDateStr=1900-01-01, acceptedDate=null, acceptedDateStr=null, onlineDate=1254067200000, onlineDateStr=2009-09-28, pubDate=1254067200000, pubDateStr=2009-09-28, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1254067200000, onlineIssueDateStr=2009-09-28, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1774073432211, creator=sys-migrate, updateTime=1774073432211, updator=sys-migrate, issue=Issue{id=1242117211490419171, tenantId=1146029695717560320, journalId=1146031591421210625, year='2009', volume='27', issue='0918', pageStart='3', pageEnd='140', issueExtLink='null', onlineDate='null', pubDate='1254067200000', pubDateStr='2009-09-28', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=3, issueType=-1, specialIssue=null, createTime=1774073420636, creator='sys-migrate', updateTime=1774073420636, updator='sys-migrate', preIssue=null, nextIssue=null, articleTotal=null, ext=null, issueFiles=null, downloadFileDto=null}, startPage=28, endPage=32, ext={EN=ArticleExt(id=1242117263348794025, articleId=1242117260031099544, tenantId=1146029695717560320, journalId=1146031591421210625, language=EN, title=Improved Image Compression Method Based on Wavelet Transform and Its Application, columnId=1242116080374710456, journalTitle=Science & Technology Review, columnName=Articles, runingTitle=null, highlight=null, articleAbstract= The lifting scheme is a new bi-orthogonal wavelet constructing method, which can effectively reduce wavelet run time. The Embedded Zero-tree Wavelet (EZW) coding algorithm makes a full use of data distribution characteristics after wavelet transform, can realize progressive image transmission and is one of the most effective image coding methods. Yet, in the EZW algorithm, low-frequency and high-frequency data are coded by the same process, which would result in the loss of more important low-frequency data in the case of a high compression ratio. Significant loss of low-frequency data would lead to a poor recovery image quality. Furthermore, the EZW algorithm has problems of space complexity as well as temporal complexity. In view of those problems, this paper proposes three improvement methods. First, the low-frequency data are adjusted to the range of [0, 255] and then are saved directly. Second, a marking matrix is set up to track the coding position, instead of the dominant table and subsidiary table in the original process. Meanwhile, the dominant and subsidiary scans are carried out for each important coefficient simultaneously. Last, one more bit of precision to the important coefficients is added in the process of the subsidiary scan. The improved EZW and the integer lifting wavelet transform are combined and applied to a practical remote vision control system of a robot arm. The two results of image compression based separately on wavelet transform and DCT are compared and the proposed method shows better performance on both the recovery image quality and running time., authors=PU Yakun, CONG Shuang, authorsList=PU Yakun;CONG Shuang, authorCompany=null, correspAuthors=null, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=PRICOTWIVS9f84sc8LmVmw==, pdfFileSize=502726, 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=1242117262346358912, articleId=1242117260031099544, tenantId=1146029695717560320, journalId=1146031591421210625, language=CN, title=基于小波变换的图像压缩改进方法及其应用, columnId=1146540929516700224, journalTitle=科技导报, columnName=研究论文, runingTitle=null, highlight=null, articleAbstract=小波提升格式是一种新的双正交小波构造方法，能够有效地减少小波变换的运行时间。嵌入式零树小波（EZW）编码算法利用小波变换后的数据分布特性，能够实现图像的渐进传输，是最有效的小波编码方法之一。由于EZW算法对低频数据和高频数据采用同样的方法进行编码，使得在压缩率较高的情况下低频数据损失较大，因而降低了复原图像的质量。EZW算法同时还不同程度地存在着空间和时间复杂度过高的问题。针对这两个问题，进行了3个方面的改进：首先，将低频数据调整到[0，255]之间后直接存储；其次，通过设置标记矩阵记录编码位置，以此取代主表和副表，并对每一个重要系数同时进行主扫描和副扫描；最后，对高频数据，将副扫描中重要系数的精度提高一个比特。将整数提升格式的小波变换算法和改进EZW编码相结合，并应用于一个实际的机械臂远程控制系统中，结果显示，新算法的实验结果与原系统中基于DCT图像压缩方法的结果相比，前者在恢复图像质量和运行时间上都显示出优越性。, authors=蒲亚坤，丛 爽, authorsList=蒲亚坤;丛 爽, authorCompany=中国科学技术大学自动化系，合肥 230026, correspAuthors=null, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=nkY4VzH1OHivvhdFj5wusA==, pdfFileSize=502726, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, 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