Evolved image compression transforms

Shawn Aldridge; Brendan Babb; Frank Moore; Michael Peterson

doi:10.1117/12.850493

15 April 2010 Evolved image compression transforms

Shawn Aldridge, Brendan Babb, Frank Moore, Michael Peterson

Proceedings Volume 7704, Evolutionary and Bio-Inspired Computation: Theory and Applications IV; 77040C (2010) https://doi.org/10.1117/12.850493
Event: SPIE Defense, Security, and Sensing, 2010, Orlando, Florida, United States

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.

Citation Download Citation

Shawn Aldridge, Brendan Babb, Frank Moore, and Michael Peterson "Evolved image compression transforms", Proc. SPIE 7704, Evolutionary and Bio-Inspired Computation: Theory and Applications IV, 77040C (15 April 2010); https://doi.org/10.1117/12.850493

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