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Optimization and Assessment of Wavelet Packet Decompositions with Evolutionary Computation

Author(s): Schell Thomas | Uhl Andreas

Journal: EURASIP Journal on Advances in Signal Processing
ISSN 1687-6172

Volume: 2003;
Issue: 8;
Start page: 298617;
Date: 2003;
Original page

Keywords: image compression | wavelet packets | best basis algorithm | genetic algorithms | random search

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.

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