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Proceedings Paper

Concept of linear run and its application to image compression
Author(s): Sukhamay Kundu
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Paper Abstract

We introduce here the motion of a linear-run in the sequence of gray values of an image. We present an optimal linear-time algorithm for decomposing an image into the smallest number of linear-runs that approximate the gray values within a given error limit (epsilon) > 0. For (epsilon) <EQ 6, which give good visual quality approximations, the linear-runs give significantly fewer runs that the traditional runs based on constant gray values in each run, and requires only about 1/3 of the memory needed for the traditional run-length method.We demonstrate the usefulness of this method on example images.

Paper Details

Date Published: 13 October 1998
PDF: 10 pages
Proc. SPIE 3455, Applications and Science of Neural Networks, Fuzzy Systems, and Evolutionary Computation, (13 October 1998); doi: 10.1117/12.326721
Show Author Affiliations
Sukhamay Kundu, Louisiana State Univ. (United States)


Published in SPIE Proceedings Vol. 3455:
Applications and Science of Neural Networks, Fuzzy Systems, and Evolutionary Computation
Bruno Bosacchi; David B. Fogel; James C. Bezdek, Editor(s)

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