Wavelet image coding using trellis coded space-frequency quantization

The progress in wavelet image coding have brought the field into its maturity. Major developments in the process are rate-distortion (R-D) based wavelet packet transformation, zerotree quantization, subband classification and trellis-coded quantization, and sophisticated context modeling in entropy...

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Bibliographic Details
Published in:IEEE signal processing letters 1999-07, Vol.6 (7), p.158-161
Main Authors: Xiong, Zixiang, Wu, Xiaolin
Format: Article
Language:English
Subjects:
Arithmetic
Coders
Coding
Context modeling
Entropy
Entropy coding
Image coding
Mathematical models
PSNR
Quantization
Rate-distortion
Transform coding
Wavelet
Wavelet coefficients
Wavelet packets
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Summary:The progress in wavelet image coding have brought the field into its maturity. Major developments in the process are rate-distortion (R-D) based wavelet packet transformation, zerotree quantization, subband classification and trellis-coded quantization, and sophisticated context modeling in entropy coding. Drawing from past experience and recent in sights, we propose a new wavelet image coding technique with trellis coded space-frequency quantization (TCSFQ). TCSFQ aims to explore space-frequency characterizations of wavelet image representations via R-D optimized zerotree pruning, trellis-coded quantization, and context modeling in entropy coding. Experiments indicate that the TCSFQ coder achieves twice as much compression as the baseline JPEG coder does at the same peak signal to noise ratio (PSNR), making it better than all other coders described in the literature.
ISSN:1070-9908
1558-2361
DOI:10.1109/97.769357