EURASIP Journal on Applied Signal Processing 
Volume 2003 (2003), Issue 8, Pages 806-813
doi:10.1155/S111086570330407X

Optimization and Assessment of Wavelet Packet Decompositions with Evolutionary Computation

Thomas Schell and Andreas Uhl

Department of Scientific Computing, University of Salzburg, Jakob Haringer Street 2, Salzburg A-5020, Austria

Received 30 June 2002; Revised 27 November 2002

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.