Skip to main content
  • Research Article
  • Published:

Optimization and Assessment of Wavelet Packet Decompositions with Evolutionary Computation

Abstract

In image compression, the wavelet transformation is a state-of-the-art component. Recently, wavelet packet decomposition has received quite an interest. A popular approach for wavelet packet decomposition is the near-best-basis algorithm using nonadditive cost functions. In contrast to additive cost functions, the wavelet packet decomposition of the near-best-basis algorithm is only suboptimal. We apply methods from the field of evolutionary computation (EC) to test the quality of the near-best-basis results. We observe a phenomenon: the results of the near-best-basis algorithm are inferior in terms of cost-function optimization but are superior in terms of rate/distortion performance compared to EC methods.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Thomas Schell.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Schell, T., Uhl, A. Optimization and Assessment of Wavelet Packet Decompositions with Evolutionary Computation. EURASIP J. Adv. Signal Process. 2003, 298617 (2003). https://doi.org/10.1155/S111086570330407X

Download citation

  • Received:

  • Revised:

  • Published:

  • DOI: https://doi.org/10.1155/S111086570330407X

Keywords