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Proceedings Paper

Space-frequency quantization for wavelet image coding
Author(s): Zixiang Xiong; Kannan Ramchandran; Michael T. Orchard
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Paper Abstract

A novel wavelet packet image coder is introduced in this paper. It is based on our previous work on wavelet image coding using space-frequency quantization (SFQ), in which zerotree quantization and scalar quantization are jointly optimized in a rate-distortion sense. In this paper, we extend the powerful SFQ coding paradigm from the wavelet transform to the more general wavelet packet transformation. The resulting wavelet packet coder offers a universal transform coding framework within the constraints of filter bank structures by allowing joint transform and quantizer design without assuming a priori statistics of the input image. In other words, the new coder adaptively chooses the representation to suit the image and the quantization to suit the representation. Experimental results show that, for some image classes, our new coder is capable of achieving the best coding performances among those in the published literature.

Paper Details

Date Published: 14 November 1996
PDF: 12 pages
Proc. SPIE 2847, Applications of Digital Image Processing XIX, (14 November 1996); doi: 10.1117/12.258247
Show Author Affiliations
Zixiang Xiong, Princeton Univ. (United States)
Kannan Ramchandran, Univ. of Illinois/Urbana-Champaign (United States)
Michael T. Orchard, Princeton Univ. (United States)


Published in SPIE Proceedings Vol. 2847:
Applications of Digital Image Processing XIX
Andrew G. Tescher, Editor(s)

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