Wavelet image coding using trellis coded space-frequency quantization Academic Article

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 insights, 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.

authors

• Xiong, Zixiang

published proceedings

• IEEE Signal Processing Letters

author list (cited authors)

• Xiong, Z., & Wu, X.

citation count

• 20

complete list of authors

• Xiong, Zixiang||Wu, Xiaolin

publication date

• July 1999

publisher

• Institute of Electrical and Electronics Engineers (IEEE)  Publisher

published in

• IEEE Signal Processing Letters  Journal

Digital Object Identifier (DOI)

• 10.1109/97.769357

start page

• 158

end page

• 161

volume

• 6

issue

• 7

URL

• http://dx.doi.org/10.1109/97.769357