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Proceedings Paper

Efficient compression of medical images through arithmetic coding
Author(s): Tenkasi V. Ramabadran; Keshi Chen
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Paper Abstract

A new method for the noiseless compression of medical images is described. The method uses the wellknown DPCM technique (i.e. , linear prediction) for decorrelating a given image. However, instead of encoding the pixels of the decorrelated image using a memoryless model as in the conventional method, a source model with several conditioning events (or contexts) is employed. The contexts are based on the horizontal and vertical components of the gradient in the given image as well as the predicted value of a pixel. The statistics under each context of the model are obtained adaptively. In order to encode the decorrelated image as an outcome of such a complex source model, the powerful arithmetic coding technique is employed. Experimental results show that the new method can compress typical medical images 20% to 30% better than the conventional method.

Paper Details

Date Published: 1 August 1990
PDF: 15 pages
Proc. SPIE 1234, Medical Imaging IV: PACS Systems Design and Evaluation, (1 August 1990); doi: 10.1117/12.19002
Show Author Affiliations
Tenkasi V. Ramabadran, Iowa State Univ. (United States)
Keshi Chen, Iowa State Univ. (United States)

Published in SPIE Proceedings Vol. 1234:
Medical Imaging IV: PACS Systems Design and Evaluation
Samuel J. Dwyer III; R. Gilbert Jost M.D., Editor(s)

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