A Visually Weighted Quantization Scheme for Image Bandwidth Compression at Low Data Rates

Source encoding of images for bandwidth compression has become attractive in recent years because of decreasing hardware costs. By combining the source encoding approach with transform coding techniques, it is possible to obtain good image quality at low data rates. The general aspects of such a system are presented. The design of the quantizer for transform coefficients, which is the major source of error associated with the compression process, is considered using a visual fidelity criterion and subject to the constraint that the entropy of the quantizer be a prespecified quantity. A visually weighted suboptimal quantization scheme is developed to take into account the relative importance of different transform coefficients to the human visual system.