Daubechies Wavelet template design of a Cellular Neural Network for Image Compression

نویسنده

  • Ramana Rao
چکیده

In the computation of forward and inverse Discrete Wavelet Transform (DWT) using Cellular Neural Network (CNN), templates that mimic Haar wavelet are used. It is well known that Daubechies wavelet is the most popular wavelet used in the computation of DWT coefficients. This paper presents an approach towards the design of templates that mimic Daubechies wavelets. A global search algorithm, namely, Particle Swarm Optimization (PSO) is used to evolve the forward and inverse DWT cloning templates. A brief overview of the PSO algorithm and the method for template evolution is presented along with the evolved cloning templates for the forward and inverse DWT. The performance of these templates is verified by a DWT based Image compression simulation. The subjective quality of the reconstructed images obtained is comparable with the direct filter implementation.

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تاریخ انتشار 2007