{"title":"Three novel lossless image compression schemes for medical image archiving and telemedicine.","authors":"J Wang, G Naghdy","doi":"10.1089/107830200415199","DOIUrl":null,"url":null,"abstract":"<p><p>In this article, three novel lossless image compression schemes, hybrid predictive/vector quantization lossless image coding (HPVQ), shape-adaptive differential pulse code modulation (DPCM) (SADPCM), and shape-VQ-based hybrid ADPCM/DCT (ADPCMDCT) are introduced. All are based on the lossy coder, VQ. However, VQ is used in these new schemes as a tool to improve the decorrelation efficiency of those traditional lossless predictive coders such as DPCM, adaptive DPCM (ADPCM), and multiplicative autoregressive coding (MAR). A new kind of VQ, shape-VQ, is also introduced in this article. It provides predictive coders useful information regarding the shape characters of image block. These enhance the performance of predictive coders in the context of lossless coding. Simulation results of the proposed coders applied in lossless medical image compression are presented. Some leading lossless techniques such as DPCM, hierarchical interfold (HINT), CALIC, and the standard lossless JPEG are included in the tests. Promising results show that all these three methods are good candidates for lossless medical image compression.</p>","PeriodicalId":79734,"journal":{"name":"Telemedicine journal : the official journal of the American Telemedicine Association","volume":"6 2","pages":"251-60"},"PeriodicalIF":0.0000,"publicationDate":"2000-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1089/107830200415199","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Telemedicine journal : the official journal of the American Telemedicine Association","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1089/107830200415199","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8
Abstract
In this article, three novel lossless image compression schemes, hybrid predictive/vector quantization lossless image coding (HPVQ), shape-adaptive differential pulse code modulation (DPCM) (SADPCM), and shape-VQ-based hybrid ADPCM/DCT (ADPCMDCT) are introduced. All are based on the lossy coder, VQ. However, VQ is used in these new schemes as a tool to improve the decorrelation efficiency of those traditional lossless predictive coders such as DPCM, adaptive DPCM (ADPCM), and multiplicative autoregressive coding (MAR). A new kind of VQ, shape-VQ, is also introduced in this article. It provides predictive coders useful information regarding the shape characters of image block. These enhance the performance of predictive coders in the context of lossless coding. Simulation results of the proposed coders applied in lossless medical image compression are presented. Some leading lossless techniques such as DPCM, hierarchical interfold (HINT), CALIC, and the standard lossless JPEG are included in the tests. Promising results show that all these three methods are good candidates for lossless medical image compression.