Extended performance comparison of hybrid wavelet transform for image compression with varying proportions of constituent transforms

The rapid growth of digital imaging applications have increased the need for effective image compression techniques. Image compression minimizes the size of the image without degrading the quality of the image to an unacceptable level. Image compression in transform domain is one of the most popular techniques. Previous work has proved that the hybrid wavelet transforms (HWT) are better than the respective constituent orthogonal transforms in image compression[1, 2]. Here the extended performance comparison of HWT for image compression is presented with varying the constituent transforms and the proportions of the constituent transforms to test the effect on quality of image compression. The experimentation is done on set of 20 images by varying the constituent transforms, proportion of constituent transforms and compression ratios (CR). The constituent transforms used to generated HWT are Cosine transform, Sine transform, Slant transform, Kekre transform, Walsh transform and Haar transform. Here five proportions of constituent transforms alias 1:16, 1:4, 1:1, 4:1, 16:1 are considered for generation of HWT. Results prove that 4:1, 1:1, 1:4 proportions of constituent transforms in HWT gives better performance as compared to 1:1 proportion of constituent transforms for different compression ratios. Also for 95% compression ratio, 4:1 ratio of DCT-Haarconstituent transforms in HWT gives better results. 1:1 ratio of DCT-Haarconstituent transforms give better results for compression ratios between 70% and 90%. For lower compression ratios, 1:4 proportions of DCT-Haarconstituent transformsin HWT gives better performance.