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Algorithm for Improved Image Compression and Reconstruction Performances

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Author(s): G.Chenchu Krishnaiah | T.Jayachandra Prasad | M.N. Giri Prasad

Journal: Signal & Image Processing
ISSN 2229-3922

Volume: 3;
Issue: 2;
Start page: 79;
Date: 2012;
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Keywords: Wavelets | EEWITA | Quantization | Multi-resolution Analysis | Image Processing | Evolved wavelets | Image compression | Algorithms | Performances and Reconstruction

ABSTRACT
Energy efficient wavelet image transform algorithm (EEWITA) which is capable of evolving non-wavelettransforms consistently outperform wavelets when applied to a large class of images subject to quantizationerror. An EEWITA can evolve a set of coefficients which describes a matched forward and inversetransform pair that can be used at each level of a multi-resolution analysis (MRA) transform to minimizethe original image size and the mean squared error (MSE) in the reconstructed image. Simulation resultsindicate that the benefit of using evolved transforms instead of wavelets increases in proportion toquantization level. Furthermore, coefficients evolved against a single representative training imagegeneralize to effectively reduce MSE for a broad class of reconstructed images. In this paper an attempthas been made to perform the comparison of the performances of various wavelets and non-wavelets.Experimental results were obtained using different types of wavelets and non-wavelets for different types ofphotographic images (color and monochrome). These results concludes that the EEWITA method iscompetitive to well known methods for lossy image compression, in terms of compression ratio (CR), meansquare error (MSE), peak signal to noise ratio (PSNR), encoding time, decoding time and transformingtime or decomposition time. This analysis will help in choosing the wavelet for decomposition of images asrequired in a particular applications.
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