Improved Binary Tree Coding for Image Compression using Modified Singular Value Decomposition

Abstract

Reducing the transmission cost while maintaining the quality of image data is the most challenging part in data transmission. In this paper, we report the possibility of improving the quality of image reconstruction by using modified singular value decomposition (SVD) and binary tree coding with adaptive scanning order (BTCA) for grayscale image compression. This method uses modified rank one updated SVD as a pre-processing step for binary tree coding to increase the quality of the reconstructed image. The high energy compaction in SVD process offers high image quality with less compression and is requires more number of bits for reconstruction. BTCA compression, also gives high image quality by coding more significant coefficients using adaptive scanning order from bottom to top with high compression rate. The proposed method uses both SVD and BTC for image compression and is tested with several test images and results are compared with those of SPIHT, JPEG, JPEG2000 and BTCA. The results show significant improvement in PSNR at high bitrates as compared to other methods.