TAILIEUCHUNG - Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2011, Article

Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2011, Article ID 973806, 20 pages doi: Research Article Evolutionary Approach to Improve Wavelet Transforms for Image Compression in Embedded Systems Rub´ n Salvador,1 F´ lix Moreno,1 Teresa Riesgo,1 and Luk´ s Sekanina2 e e aˇ 1 Centre of Industrial Electronics, Universidad Polit´cnica de Madrid, Jos´ Gutierrez Abascal 2, e e 28006 Madrid, Spain 2 Faculty of Information Technology, Brno University of Technology, Bozetechova 2, 612 66 Brno, Czech Republic Correspondence should be addressed to Rub´ n Salvador, e Received 21 July 2010; Revised 19 October 2010; Accepted 30 November 2010 Academic. | Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2011 Article ID 973806 20 pages doi 2011 973806 Research Article Evolutionary Approach to Improve Wavelet Transforms for Image Compression in Embedded Systems Ruben Salvador 1 Felix Moreno 1 Teresa Riesgo 1 and Lukas Sekanina2 1 Centre of Industrial Electronics Universidad Politecnica de Madrid Jose Gutierrez Abascal 2 28006 Madrid Spain 2 Faculty of Information Technology Brno University of Technology Bozetechova 2 612 66 Brno Czech Republic Correspondence should be addressed to Ruben Salvador Received 21 July 2010 Revised 19 October 2010 Accepted 30 November 2010 Academic Editor Yannis Kopsinis Copyright 2011 Ruben Salvador et al. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. A bioinspired evolutionary algorithm for optimizing wavelet transforms oriented to improve image compression in embedded systems is proposed modelled and validated here. A simplified version of an Evolution Strategy using fixed point arithmetic and a hardware-friendly mutation operator has been chosen as the search algorithm. Several cutdowns on the computing requirements have been done to the original algorithm adapting it for an FPGA implementation. The work presented in this paper describes the algorithm as well as the test strategy developed to validate it showing several results in the effort to find a suitable set of parameters that assure the success in the evolutionary search. The results show how high-quality transforms are evolved from scratch with limited precision arithmetic and a simplified algorithm. Since the intended deployment platform is an FPGA HW SW partitioning issues are also considered as well as code profiling accomplished to validate the proposal showing some preliminary results of the .

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