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Proceedings Paper

Evolved image compression transforms
Author(s): Shawn Aldridge; Brendan Babb; Frank Moore; Michael Peterson
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Paper Abstract

State-of-the-art image compression and reconstruction schemes utilize wavelets. Quantization and thresholding are commonly used to achieve additional compression, but cause permanent, irreversible information loss. This paper describes an investigation into whether evolutionary computation (EC) may be used to optimize forward (compression-only) transforms capable of matching or exceeding the compression capabilities of a selected wavelet, while reducing the aggregate error in images subsequently reconstructed by that wavelet. Transforms are independently trained and tested using three sets of images: digital photographs, fingerprints, and satellite images.

Paper Details

Date Published: 15 April 2010
PDF: 10 pages
Proc. SPIE 7704, Evolutionary and Bio-Inspired Computation: Theory and Applications IV, 77040C (15 April 2010); doi: 10.1117/12.850493
Show Author Affiliations
Shawn Aldridge, Univ. of Alaska Anchorage (United States)
Brendan Babb, Univ. of Alaska Anchorage (United States)
Frank Moore, Univ. of Alaska Anchorage (United States)
Michael Peterson, Univ. of Hawaii at Hilo (United States)


Published in SPIE Proceedings Vol. 7704:
Evolutionary and Bio-Inspired Computation: Theory and Applications IV
Teresa H. O'Donnell; Misty Blowers; Kevin L. Priddy, Editor(s)

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