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Optimization of Parameterized Compactly Supported Orthogonal Wavelets for Data Compression

2011; Springer Science+Business Media; Linguagem: Inglês

10.1007/978-3-642-25330-0_45

1611-3349

Oscar Herrera-Alcántara, Miguel González-Mendoza,

Image Processing Techniques and Applications

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.