Comparative Analysis of Transform based Lossy Image Compression Techniques

We undertake a study of the performance difference of the discrete cosine transform (DCT) and the wavelet transform for gray scale images. Wide range of gray scale images were considered under seven different types of images. Image types considered in this work are standard test images, sceneries, faces, misc, textures, aerials and sequences. Performance analysis is carried out after implementing the techniques in Matlab. Reconstructed Image Quality values for every image type would be calculated over particular bit rate and would be displayed in the end to detect the quality and compression in the resulting image and resulting performance parameter would be indicated in terms of PSNR , i.e. Peak Signal to Noise Ratio. Testing is performed on seven types of images by evaluating average PSNR values. Our studies reveal that, for gray scale images, the wavelet transform outperforms the DCT at a very low bit rates and typically gave a average around 10% PSNR performance improvement over the DCT due to its better energy compaction properties. Where as DCT gave a average around 8% PSNR performance improvement over the Wavelets at high bit rates near about 1bpp and above it. So Wavelets provides good results than DCT when more compression is required.