A STUDY OF VECTOR TRANSFORM CODING OF SUBBAND-DECOMPOSED IMAGES

This paper reports our study on vector transform coding (VTC), a new image coding scheme, on subband-decomposed images. It is shown that vector transformation (VT) reduces the inter-vector correlation, although not as much as the discrete cosine transform (DCT). However, it is also shown that VT preserves the intra-vector correlation much better than the DCT so that vector quantization (VQ) in the VT domain can be made more efficient. VTC of subband-decomposed image introduces another dimension of adaptivity, in which coding parameters, bit allocation, and VQ codebooks can be adapted to each level of the subband pyramid as well as to each vector in the VT domain. The new subband/VTC scheme is compared with VQ of original images, VQ of subband-decomposed images, DCT-based transform coding, and subband/DCT/VQ schemes. Simulation results indicate that the new scheme achieves 1 to 3dB improvement over the other schemes in terms of peak signal-to-noise ratio (PSNR). This improvement is also supported by subjective evaluations.