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Improved Evolutionary Search for Image Reconstruction Transforms
- 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.
- Subjects :
- Discrete wavelet transform
business.industry
Quantization (signal processing)
Second-generation wavelet transform
Stationary wavelet transform
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
Wavelet transform
Pattern recognition
Data_CODINGANDINFORMATIONTHEORY
Iterative reconstruction
Wavelet
Artificial intelligence
business
Mathematics
Data compression
Subjects
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