Efficiency evaluation of different wavelets for image compression

In this paper, application to image processing and image compression using the discrete wavelet transform (DWT) is presented. We show the impact of the spectral distribution of the images on the quality of the image compression technique. Four families of wavelets are considered: 1) Bi-orthogonal, 2) Daubechies, 3) Coiflet and 4) Symlet. Since the good basis wavelet recommended for DWT compressor may depend on the choice of test images, we consider three test images with different but moderate spectral activities. We then evaluate the performance of the four wavelets families on each test image. A comparative results for several wavelets used in DWT compression techniques are presented using the peak signal to noise ratio (PSNR) and compression ratio (CR) as a measure of quality. Finally, we present the comparative result according to PSNR versus CR for four families of wavelets, showing that bior4.4 yields a better performance than the other Wavelets in terms of tradeoff between PSNR and CR.

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