1 October 1990 Perceptually tuned sub-band image coder
Author Affiliations +
Abstract
In this paper we present a sub-band coder for true color images that uses an empirically derived perceptual masking model to set the allowable quantization noiselevel not only for each sub-band but also for each pixel in a given sub-band. The input image is converted into YIQ space and each channel is passed through a separable Generalized Quadrature Mirror Filterbank (GQMF). This separates the image's frequency content into into 4 equal width bands in both the horizontal and vertical dimension, resulting in a representation consisting of 16 sub-bands for each channel. Using this representation, a perceptual masking model is derived for each channel. The model incorporates spatial-frequency sensitivity, contrast sensitivity, and texture masking. Based on the image dependent information in each sub-band and the perceptual masking model, noise-level targets are computed for each point in a subband. These noise-level targets are used to set the quantization levels in a DPCM quantizer. The output from the DPCM quantizer is then encoded, using an entropybased coding scheme, in either lxi , 1x2, or 2x2 pixel parts, based on the the statistics in each 4x4 sub-block of a particular sub-band. One set of codebooks, consisting of 100,000 entries, is used for all images. A block elimination algorithm takes advantage of the peaky spatial energy distribution of sub-bands to avoid using bits for quiescent parts of a given sub-band. The resultant bitrate depends on the complexity of the input image. For the images we use, high quality output requires bitrates from 0.25 to 1 .25 bits/pixel, while nearly transparent quality requires 0.5 to 2.5 bits/pixel.
© (1990) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Robert J. Safranek, James D. Johnston, Ruth Ellen Rosenholtz, "Perceptually tuned sub-band image coder", Proc. SPIE 1249, Human Vision and Electronic Imaging: Models, Methods, and Applications, (1 October 1990); doi: 10.1117/12.19678; https://doi.org/10.1117/12.19678
PROCEEDINGS
10 PAGES


SHARE
Back to Top