Title :
Data compression by multiresolution wavelet packet tree search
Author :
Patwiwat, B. ; Chu, C.H. ; Lursinsap, C.
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. This 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, and performance is measured based on the reconstruction distortion
Keywords :
data compression; genetic algorithms; matrix decomposition; signal reconstruction; trees (mathematics); wavelet transforms; adaptation scheme; data compression; decomposition step; genetic algorithm search; multiresolution wavelet packet tree; processing steps; reconstruction distortion; signal processing task; Binary trees; Biological cells; Data compression; Distortion measurement; Genetic algorithms; Magnetic resonance imaging; Optimization methods; Signal processing algorithms; Signal resolution; Wavelet packets; Wavelet transforms;
Conference_Titel :
Circuits and Systems, 1994., Proceedings of the 37th Midwest Symposium on
Conference_Location :
Lafayette, LA
Print_ISBN :
0-7803-2428-5
DOI :
10.1109/MWSCAS.1994.518969
