Block wavelet transform coding of images using classified vector quantization

A new coding scheme for image compression using classified two-channel conjugate vector quantization (TCCVQ) of the wavelet coefficients is proposed. This scheme exploits residual correlation among different layers of the discrete wavelet transform (DWT) domain and thereby improves the encoding efficiency by taking advantage of the DWT and TCCVQ, which requires less computational complexity and less storage (memory). In this scheme, DWT coefficients are rearranged to form the small blocks, which are composed of the corresponding coefficients from all subbands. The block matrices, then, are classified and further divided into subvectors depending on the DWT coefficient statistics as this allows efficient distribution of bits. Simulation results show that the reconstructed images preserve fine and pleasant qualities based on both subjective and mean square error criteria at a bit rate of 0.3 bit/pel (bpp)