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Optical Engineering

Modification of standard image compression methods for correlation-based pattern recognition
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Paper Abstract

Standard image compression algorithms may not perform well in compressing images for pattern recognition applications, since they aim at retaining image fidelity in terms of perceptual quality rather than preserving spectrally significant information for pattern recognition. New compression algorithms for pattern recognition are therefore investigated, which are based on the modification of the standard compression algorithms to simultaneously achieve higher compression ratio and improved pattern recognition performance. This is done by emphasizing middle and high frequencies and discarding low frequencies according to a new distortion measure for compression. The operations of denoising, edge enhancement, and compression can be integrated in the same encoding process in the proposed compression algorithms. Simulation results show the effectiveness of the proposed compression algorithms.

Paper Details

Date Published: 1 August 2004
PDF: 8 pages
Opt. Eng. 43(8) doi: 10.1117/1.1765664
Published in: Optical Engineering Volume 43, Issue 8
Show Author Affiliations
Mo Chen, Binghamton Univ. (United States)
Shuqun Zhang, CUNY/College of Staten Island (United States)
Mohammad A. Karim, Old Dominion Univ. (United States)


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