Paper Info
Title
Optimization of parameterized compactly supported orthogonal wavelets for data compression
Abstract
In this work we review the parameterization of filter coefficients of compactly supported orthogonal wavelets used to implement the discrete wavelet transform. We also present the design of wavelet based filters as a constrained optimization problem where a genetic algorithm can be used to improve the compression ratio on gray scale images by minimizing their entropy and we develop a quasi-perfect reconstruction scheme for images. Our experimental results report a significant improvement over previous works and they motivate us to explore other kinds of perfect reconstruction filters based on parameterized tight frames.
Year
DOI
Venue
2011
10.1007/978-3-642-25330-0_45
MICAI (2)
Keywords
Field
DocType
parameterized compactly,quasi-perfect reconstruction scheme,gray scale image,compression ratio,genetic algorithm,data compression,optimization problem,discrete wavelet,filter coefficient,perfect reconstruction,orthogonal wavelet
Parameterized complexity,Mathematical optimization,Computer science,Fast wavelet transform,Algorithm,Compression ratio,Discrete wavelet transform,Data compression,Genetic algorithm,Filter design,Wavelet
Conference
Volume
ISSN
Citations 
7095
0302-9743
1
PageRank 
References 
Authors
0.39
5
2
Name
Order
Citations
PageRank
Oscar Herrera Alcántara153.23
Miguel González Mendoza242.46