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Proceedings Paper

Progressive transmission of high-fidelity radiographic images at very low bit rates
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Paper Abstract

Compression of medical images has always been viewed with skepticism since the loss of information involved is thought to affect diagnostic information. Recent reports, however, indicate that some wavelet based compression techniques may not effectively reduce the image quality even when subjected to compression ratios (CRs) up to 30:1. Although generation of minimum distortion at a specific bit rate by vector quantization (VQ) has been theoretically proven from rate distortion theory almost half a century ago, practical implementation of VQ for small sizes and classes of images has been accomplished relatively recently. Many of the earlier algorithms using simple statistical clustering suffer from a number of problems namely lack of convergence, getting trapped in local minima, and inability to handle large datasets. More advanced vector quantization algorithms have eliminated some of the above problems. However, vector quantization of large data sets as encountered in many medical images still remains a challenging problem. We present here an adaptive vector quantization technique including an entropy coding module that is capable of encoding large size radiographic as well as color images with minimum distortion in the decoded images even at CRs above 100:1.

Paper Details

Date Published: 21 May 1999
PDF: 10 pages
Proc. SPIE 3661, Medical Imaging 1999: Image Processing, (21 May 1999); doi: 10.1117/12.348565
Show Author Affiliations
Shuyu Yang, Texas Tech Univ. (United States)
Sunanda Mitra, Texas Tech Univ. (United States)


Published in SPIE Proceedings Vol. 3661:
Medical Imaging 1999: Image Processing
Kenneth M. Hanson, Editor(s)

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