Use of a human visual model in subband coding of color video signal with adaptive chrominance signal vector quantization
Dominique Barba, José Hanen · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1991
This paper deals with vector quantization of sub-band video color images with a high visual quality. If lots of papers have already been published about the use of both techniques for monochrome still images, few of them work with color images. Our work concerns the use of some important human visual system properties to derive an optimized vector quantization of sub-band decomposed TV images. Two major properties are used. First, spatial frequency dependence in the fovea filtering is pushed into a distortion measure for vector quantization. Secondly, and perhaps the most important is that the codebook design is performed in the splitting algorithm by incorporating two complementary thresholds in the global evaluation of the distortion for each class of the code book : a visibility threshold and an annoyance threshold. With these techniques we designed optimized codebooks (with or without classification) which allowed visual vector quantizing of the chrominance component of color video digital signal without any visible impairment and with a high compression ratio.