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Evolutionary Approach to Improve Wavelet Transforms for Image Compression in Embedded Systems


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 proposed hardware architecture.

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Correspondence to Rubén Salvador.

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Salvador, R., Moreno, F., Riesgo, T. et al. Evolutionary Approach to Improve Wavelet Transforms for Image Compression in Embedded Systems. EURASIP J. Adv. Signal Process. 2011, 973806 (2011).

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  • Mutation Operator
  • Embed System
  • Evolutionary Approach
  • Image Compression
  • Test Strategy