Image Compression by Discrete Curvelet Wrapping Technique with Simplified SPHIT

Abstract

The proposed paper is to develop an efficient compression scheme and to obtain better quality and higher compression ratio through discrete curvelet transform and embedded coding of curvelet coefficients through improved Set Partitioning In Hierarchical Trees algorithm (SPIHT) algorithm. The paper demonstrates a significant improvement in visual quality and faster encoding and decoding than the wavelet with SPHIT compression. The SPHIT with wavelet compression fail to represents discontinuous along the curves. The curvelet transform is a multiscale directional transform, which allows an almost optimal non adaptive sparse representation of objects with edges. By using improved SPHIT with Curvelets model the transform coefficients based on probability of significance, at a fixed threshold of the offspring. As far as objective quality assessment of the image compression of the proposed work will gives improved Peak Signal to Noise Ratio (PSNR) and high compression ratio (CR) compared with the existing wavelet transform with SPHIT image compression.