Transform coding of images using fixed-rate and entropy-constrained trellis coded quantization
Publisher
The University of Arizona.Rights
Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.Abstract
Trellis coded quantization (TCQ) is incorporated into a transform coding structure for encoding monochrome and color images at 1 bit/pixel. Both fixed-rate and entropy-constrained designs are considered. For monochrome images, the fixed-rate TCQ-based systems provide gains in peak-signal-to-noise ratio (PSNR) of up to 3.32 dB over scalar quantizer-based systems, while the entropy-constrained designs provide gains of up to 7.50 dB. Gains in PSNR for color images of up to 1.76 dB and 3.93 dB are achieved for the fixed-rate and entropy-constrained TCQ-based systems, respectively. The high frequency background noise and fuzziness produced by scalar quantizer-based systems are virtually eliminated by the TCQ-based systems.Type
textThesis-Reproduction (electronic)