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Proceedings Paper

Sunset: a hardware-oriented algorithm for lossless compression of gray-scale images
Author(s): Glen G. Langdon Jr.
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Paper Abstract

Sunset is a lossless gray scale compression algorithm designed for a simple hardware implementation based on the prediction error context approach for predictive gray-scale compression. Sunset uses adaptive binary arithmetic coding with neighboring prediction error buckets as compact conditioning contexts for directly encoding the prediction error. A prototype card was built to send or receive either compressed or uncompressed images across the IBM PC/AT bus. A special interface was designed to load the memory buffer of a high resolution color display. The result is a component of a workstation prototype for radiologists and the physician who referred the patient. The Sunset approach handles gray scale images where the bits-per-pel precision is simply an input parameter to the algorithm; the compression algorithm itself is relatively insensitive to this parameter. For hardware simplicity, the error bucket (bin) identifier is determined by a leading-one detector (or priority encoder) circuit on the prediction error so the number of prediction error values per bucket is a power of two. The next less significant bits of the prediction error become the ''extra-bits'' which, when encoded, make the algorithm lossless. The number of extra-bits in a final (catch-all) bucket depends on the bits-per-pel parameter of the uncompressed image.

Paper Details

Date Published: 1 May 1991
PDF: 11 pages
Proc. SPIE 1444, Medical Imaging V: Image Capture, Formatting, and Display, (1 May 1991); doi: 10.1117/12.45179
Show Author Affiliations
Glen G. Langdon Jr., Univ. of California/Santa Cruz and IBM/Almaden Research Ctr. (United States)

Published in SPIE Proceedings Vol. 1444:
Medical Imaging V: Image Capture, Formatting, and Display
Yongmin Kim, Editor(s)

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