{"title":"Progressive near-lossless coding of medical images","authors":"A. Krivoulets","doi":"10.1109/ISPA.2003.1296894","DOIUrl":null,"url":null,"abstract":"We propose an algorithm intended for compression of medical images, which allows for embedded coding in L/sub /spl infin// sense, i.e., progressive near-lossless as well as lossless image compression. The method is based on a lossy plus near-lossless layered compression scheme and embedded quantization of the difference signal. We show, that this technique allows for a better image quality and compression performance for large tolerance values than algorithms based on predictive coding. The lossy plus near-lossless scheme also allows for image reconstruction with a minimum mean square error (MSE) criterion, while providing a strict control of the maximum absolute difference error. This property is impossible in predictive coding algorithms.","PeriodicalId":218932,"journal":{"name":"3rd International Symposium on Image and Signal Processing and Analysis, 2003. ISPA 2003. Proceedings of the","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2003-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"3rd International Symposium on Image and Signal Processing and Analysis, 2003. ISPA 2003. Proceedings of the","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISPA.2003.1296894","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
We propose an algorithm intended for compression of medical images, which allows for embedded coding in L/sub /spl infin// sense, i.e., progressive near-lossless as well as lossless image compression. The method is based on a lossy plus near-lossless layered compression scheme and embedded quantization of the difference signal. We show, that this technique allows for a better image quality and compression performance for large tolerance values than algorithms based on predictive coding. The lossy plus near-lossless scheme also allows for image reconstruction with a minimum mean square error (MSE) criterion, while providing a strict control of the maximum absolute difference error. This property is impossible in predictive coding algorithms.