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Proceedings Paper

Comparison Of Discrete Cosine Transform And Vector Quantization Of Medical Imagery
Author(s): Barry G. Haskell; Hsueh-Ming Hang
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Paper Abstract

This paper addresses the problem of data compression of medical imagery such as X-rays, Computer Tomography, Magnetic Resonance, Nuclear Medicine and Ultrasound. The Discrete Cosine Transform (DCT) has been extensively studied for image data compression, and good compression has been obtained without unduly sacrificing image quality. Vector Quantization has only recently been applied to image data compression, but shows promise of outperforming more traditional transform coding methods, especially at high compression. Vector Quantization is quite well suited for those applications where the images to be processed are very much alike, or can be grouped into a small number of classifications. These and similar studies continue to suffer from the lack of a uniformly agreed upon measure of image quality. This is also exacerbated by the large variety of electronic displays and viewing conditions.

Paper Details

Date Published: 12 June 1986
PDF: 11 pages
Proc. SPIE 0626, Application of Optical Instrumentation in Medicine XIV and Picture Archiving and Communication Systems, (12 June 1986); doi: 10.1117/12.975421
Show Author Affiliations
Barry G. Haskell, AT&T Bell Laboratories (United States)
Hsueh-Ming Hang, AT&T Bell Laboratories (United States)


Published in SPIE Proceedings Vol. 0626:
Application of Optical Instrumentation in Medicine XIV and Picture Archiving and Communication Systems
Samuel J. Dwyer; Roger H. Schneider, Editor(s)

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