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Improved Evolutionary Search for Image Reconstruction Transforms

Authors :
Michael R. Peterson
Frank W. Moore
Gary B. Lamont
Source :
IEEE Congress on Evolutionary Computation
Publication Year :
2006
Publisher :
IEEE, 2006.

Abstract

Lossy image compression algorithms sacrifice perfect image reconstruction in favor of decreased storage requirements. Previous research demonstrates that a genetic algorithm can improve image reconstruction in the presence of quantization error by replacing the wavelet reconstruction coefficients with a set of evolved coefficients. This paper expands previous research efforts by using an improved fitness function, exploring standard versus local genetic search operators, and evolving coefficient sets that perform quite well for multi-resolution analysis (MRA). Test results indicate that our improved evolutionary system consistently outperforms the standard discrete wavelet transform (DWT) for image reconstruction under compression conditions which are subject to quantization error.

Details

Database :
OpenAIRE
Journal :
2006 IEEE International Conference on Evolutionary Computation
Accession number :
edsair.doi...........43ddd2bb0a35e921d3397bbe5ba9148e
Full Text :
https://doi.org/10.1109/cec.2006.1688671