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Proceedings Paper

Image splitting and remapping method for radiological image compression
Author(s): Shih-Chung Benedict Lo; Ellen L. Shen; Seong Ki Mun
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Paper Abstract

A new decomposition method using image splitting and gray-level remapping has been proposed for image compression, particularly for images with high contrast resolution. The effects of this method are especially evident in our radiological image compression study. In our experiments, we tested the impact of this decomposition method on image compression by employing it with two coding techniques on a set of clinically used CT images and several laser film digitized chest radiographs. One of the compression techniques used was full-frame bit-allocation in the discrete cosine transform domain, which has been proven to be an effective technique for radiological image compression. The other compression technique used was vector quantization with pruned tree-structured encoding, which through recent research has also been found to produce a low mean-square-error and a high compression ratio. The parameters we used in this study were mean-square-error and the bit rate required for the compressed file. In addition to these parameters, the difference between the original and reconstructed images will be presented so that the specific artifacts generated by both techniques can be discerned by visual perception.

Paper Details

Date Published: 1 July 1990
PDF: 10 pages
Proc. SPIE 1232, Medical Imaging IV: Image Capture and Display, (1 July 1990); doi: 10.1117/12.18870
Show Author Affiliations
Shih-Chung Benedict Lo, Georgetown Univ. (United States)
Ellen L. Shen, Massachusetts Institute of Technology (United States)
Seong Ki Mun, Georgetown Univ. (United States)

Published in SPIE Proceedings Vol. 1232:
Medical Imaging IV: Image Capture and Display
Yongmin Kim, Editor(s)

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