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A filter banks design using a multi-objective genetic algorithm for embedded image coding scheme

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4 Author(s)
A. Boukhobza ; RCAM Laboratory of research, University of Sidi-Bel Abbes, Algeria ; A. Taleb Ahmed ; A. Bounoua ; N. Taleb

A multi-objective genetic algorithm for the design of biorthogonal filter banks for embedded image coding application is presented. To be effective, the filter bank would satisfy multiple requirements related to such application. Flexibility in the design is introduced by imposing Near Perfect Reconstruction (N-PR) condition instead of entire PR condition as in conventional designs. Especially for embedded coding purposes, the filter banks are designed to be near-orthogonal. This can only be made possible by minimizing the deviation from the orthogonality in the optimization process. The optimization problem is formulated as a constrained multi-objective problem and solved using a constrained Non-dominated sorting genetic algorithm (C-NSGA) by searching solutions that achieve the best compromise between the different objective criteria, these solutions are known as Pareto Optimal Solutions. Experiment results show that our designed filter banks lead to improved performances of image coding compared to those achieved by the 9/7 filter bank of JPEG2000.

Published in:

Image and Signal Processing and Analysis, 2009. ISPA 2009. Proceedings of 6th International Symposium on

Date of Conference:

16-18 Sept. 2009