JOURNAL ARTICLE

Universal trellis coded quantization

James H. KasnerMichael W. MarcellinB.R. Hunt

Year: 1999 Journal:   IEEE Transactions on Image Processing Vol: 8 (12)Pages: 1677-1687   Publisher: Institute of Electrical and Electronics Engineers

Abstract

A new form of trellis coded quantization based on uniform quantization thresholds and "on-the-fly" quantizer training is presented. The universal trellis coded quantization (UTCQ) technique requires neither stored codebooks nor a computationally intense codebook design algorithm. Its performance is comparable with that of fully optimized entropy-constrained trellis coded quantization (ECTCQ) for most encoding rates. The codebook and trellis geometry of UTCQ are symmetric with respect to the trellis superset. This allows sources with a symmetric probability density to be encoded with a single variable-rate code. Rate allocation and quantizer modeling procedures are given for UTCQ which allow access to continuous quantization rates. An image coding application based on adaptive wavelet coefficient subblock classification, arithmetic coding, and UTCQ is presented. The excellent performance of this coder demonstrates the efficacy of UTCQ. We also present a simple scheme to improve the perceptual performance of UTCQ for certain imagery at low bit rates. This scheme has the added advantage of being applied during image decoding, without the need to reencode the original image.

Keywords:
Codebook Trellis quantization Quantization (signal processing) Algorithm Linde–Buzo–Gray algorithm Entropy encoding Mathematics Decoding methods Coding (social sciences) Entropy (arrow of time) Huffman coding Computer science Data compression Image compression Image processing Artificial intelligence Image (mathematics) Statistics

Metrics

80
Cited By
7.84
FWCI (Field Weighted Citation Impact)
18
Refs
0.98
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Advanced Data Compression Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Image and Signal Denoising Methods
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Advanced Image Processing Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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