Title :
Genetic algorithm approach to the configuration of wavelet packet processing tree
Author_Institution :
Center for Adv. Comput. Studies, Southwestern Louisiana Univ., Lafayette, LA, USA
Abstract :
The standard wavelet transform can be considered to be a subtree of a complete multiresolution binary tree, in which each branch corresponds to a decomposition step. Any subtree of this multiresolution tree which covers all leaves is a valid wavelet packet processing tree, which specifies the processing steps for a wavelet decomposition of the original data. The present paper describes an adaptation scheme for configuring a wavelet packet processing tree using a genetic algorithm search of the complete multiresolution tree. Data compression is used as the target signal processing task. Trees are configured for different compression rates, and performance is measured based on the reconstruction distortion. Performances are validated using testing as well as training data; the performance of the configured trees are compared to that of the standard wavelet transform
Keywords :
data compression; data compression; genetic algorithm; multiresolution binary tree; subtree; target signal processing; wavelet decomposition; wavelet packet processing tree; wavelet transform; Binary trees; Data compression; Distortion measurement; Genetic algorithms; Performance evaluation; Signal processing algorithms; Signal resolution; Testing; Wavelet packets; Wavelet transforms;
Conference_Titel :
Pattern Recognition, 1994. Vol. 3 - Conference C: Signal Processing, Proceedings of the 12th IAPR International Conference on
Conference_Location :
Jerusalem
Print_ISBN :
0-8186-6275-1
DOI :
10.1109/ICPR.1994.577121