Subband/VQ coding of color images with perceptually optimal bit allocation

Subband coding and vector quantization combined can provide a powerful method for compressing color images. The use of properties of the human visual system can increase the performance of such a system and allow one to achieve very high quality reconstructed images at compression ratios exceeding 10:1. The authors design a color subband-vector quantization system, and formulate the bit allocation problem as an optimization problem where the objective function depends on the distortion-rate curves of the quantizers and on a set of perceptual weights. These weights are derived from data provided by measurements of the mean detection threshold of the human visual system for color transitions along the luminance, red-green, and blue-yellow directions. Minimization of the objective function constrained by the desired bit rate gives a perceptually optimal bit allocation. Three subband/VQ cases are examined. In the first two cases (case 1 and case 2), the color components of the lowest frequency subband are scalar quantized. Case 1 combines the three color components of each pixel of the higher frequency subbands into a three-dimensional vector, while case 2 creates four-dimensional vectors from 2×2 blocks in each subband color component. The third case (case 3) is the same as case 2, except that the chrominance components of the lowest frequency subband are also vector quantized with 2×2 blocks in each component. To obtain the required compression ratio and the high color fidelity required for HDTV applications, the vector quantization is done in C.I.E. L*a*b* space and AC₁C₂ space