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Proceedings Paper

Lossy compression of medical images using prediction and classification
Author(s): Heesub Lee; Yongmin Kim; Alan H. Rowberg; Mark S. Frank M.D.; Woobin Lee
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Paper Abstract

In this paper, a lossy image compression algorithm based on a prediction and classification scheme is discussed. The algorithm decomposes an image into four subimages by subsampling pixels at even and odd row and column locations. Since the four subimages have strong correlations to one another, one of them is used in predicting all the others and the resulting differences between the predicted subimages and the original subimages are encoded. Estimated differences tend to be large in a region where pixel values change rapidly, while the differences are small in a monotonous region. This redundancy is explored by dividing the estimated differences into subsets based on the slope of pixel changes, the basis for which is found in some human perception models used to measure the visibility of distortion. The resulting classified estimated differences having different visibilities are encoded with classified vector quantizers.

Paper Details

Date Published: 30 June 1993
PDF: 9 pages
Proc. SPIE 1897, Medical Imaging 1993: Image Capture, Formatting, and Display, (30 June 1993); doi: 10.1117/12.146976
Show Author Affiliations
Heesub Lee, Univ. of Washington (United States)
Yongmin Kim, Univ. of Washington (United States)
Alan H. Rowberg, Univ. of Washington (United States)
Mark S. Frank M.D., Univ. of Washington (United States)
Woobin Lee, Univ. of Washington (United States)

Published in SPIE Proceedings Vol. 1897:
Medical Imaging 1993: Image Capture, Formatting, and Display
Yongmin Kim, Editor(s)

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