Comparison of SPIHT and Lifting Scheme Image Compression Techniques for Satellite Imageries

Abstract

offer an elegant technique for representing the levels of details present in an image. When an image is decomposed using wavelets, the low pass components carry more information than the high pass components. The possibility of better elimination of high pass components gives higher compression ratio for wavelet based techniques. To achieve higher compression ratio, various coding schemes have been considered. The study of 2-D Discrete Wavelet Technique (DWT) architectures reveals that there are two schemes for implementing DWT, one is based on convolution and other based on lifting scheme. . In the present paper a detailed study of the lifting compression scheme for satellite imageries has been carried out. A comparison between the performance of the lifting scheme and SPHIT technique has been made in the context of satellite imageries. For a given compression ratio, the PSNR (peak signal to noise ratio) values are estimated for both the schemes to achieve better quality of the reconstructed image. The results of the analysis demonstrate that for both the schemes, the PSNR values increases with the level of decomposition. The results of the analysis further indicates that for satellite imageries, the lifting scheme is more efficient for obtaining higher compression ratio ~8 and better PSNR values ~29 for achieving good quality of the reconstructed image.