Optimization of Parameterized Compactly Supported Orthogonal Wavelets for Data Compression

  • Oscar Herrera Alcántara
  • Miguel González Mendoza
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7095)


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.


Wavelets parameterization optimization data compression entropy genetic algorithm 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Oscar Herrera Alcántara
    • 1
  • Miguel González Mendoza
    • 2
  1. 1.Departamento de SistemasUniversidad Autónoma Metropolitana AzcapotzalcoMéxico
  2. 2.División de Ingeniería y ArquitecturaITESM-CEM, Carretera al Lago de GuadalupeMéxicoMéxico

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