Visual Weighted SPECK Image Coding Based on WBCT

Wavelet transform is not the optimal or the most sparse function representation for two-dimension images. Contourlet transform, as a kind of Multi-scale Geometric Analysis (MGA) methods, extends the advantages of wavelet transform to high dimensional space. It can describe the properties of high dimensional information better and is more suitable for processing information with hyper-plane singularity. In this paper, a visual weighted image coding algorithm was proposed, in which Wavelet-Based Contourlet Transform (WBCT) was combined with SPECK algorithm. According to the sensitivity of human vision to different wavelet sub-bands, each sub-band was endued with different weights. The wavelet coefficients were organized in way of set partitioning and SPECK algorithm was applied to carry out image coding procedure. Experiment results show that the proposed method not only improve the Peak Signal-to-Noise Ratio (PSNR) of the reconstructed images, but also reduce the local texture distortion obviously.