Lossless Image Compression Using Traditional and Lifting Based Wavelet Transforms

In this paper an attempt has been made to analyse different wavelet techniques for image compression. Both hand-designed and lifting based wavelets are considered. Hand designed wavelets considered in this work are Haar wavelet, Daubechie wavelet, Biorthognal wavelet, Demeyer wavelet, Coiflet wavelet and Symlet wavelet. Lifting based wavelet transforms considered are 5/3 and 9/7. Wide range of images, including both color and gray scale images were considered. These wavelet transforms are used to compress the test images competitively by using Set Partitioning In Hierarchical Trees (SPIHT) algorithm and by incorporating lifting concepts. Set Partitioning In Hierarchical Trees is a new advanced algorithm based on wavelet transform which is gaining attention due to many potential commercial applications in the area of image compression. These algorithms resulted in practical advantages, such as, superior low bit rate performance, bit-level compression, progressive transmission by pixel, accuracy and resolution .The SPIHT coder is also a highly refined version of the EZW algorithm and is a powerful image compression algorithm, that produces an embedded bit stream form, in which the best reconstructed images shows a significant perceptual improvement as well as an increased PSNR. K Purnima Student of M.Tech AVSCET, Venkatachalam TV Sampath Kumar Professor AVSCET, Venkatachalam ISSN 2319-9725 May, 2013 www.ijirs.com Vol 2 Issue 5 International Journal of Innovative Research and Studies Page 65