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Proceedings Paper

Wavelet image coding using trellis-coded space-frequency quantization
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Paper Abstract

Recent progresses 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 insight, 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.

Paper Details

Date Published: 28 December 1998
PDF: 9 pages
Proc. SPIE 3653, Visual Communications and Image Processing '99, (28 December 1998); doi: 10.1117/12.334678
Show Author Affiliations
Zixiang Xiong, Univ. of Hawaii (United States)
Xiaolin Wu, Univ. of Western Ontario (Canada)


Published in SPIE Proceedings Vol. 3653:
Visual Communications and Image Processing '99
Kiyoharu Aizawa; Robert L. Stevenson; Ya-Qin Zhang, Editor(s)

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