Vector set partitioning with classified successive refinement VQ for embedded wavelet image coding

Debargha Mukherjee and Sanjit K. Mitra
Image Processing Laboratory
Department of Electrical and Computer Engineering,
University of California, Santa Barbara, CA 93106.
Email: (debu,mitra)


Set Partitioning in Hierarchical Trees (SPIHT), proposed by Said and Pearlman 1, is generally regarded as a very efficient wavelet-based still image compression scheme. The algorithm uses an efficient, joint scanning and bit-allocation mechanism for quantizing the scalar wavelet coefficients, and produces a perfectly embedded bitstream. This work extends set partitioning to scan vectors of wavelet coefficients, and use successive refinement VQ techniques such as multistage and tree-structured VQ, to quantize several wavelet coefficients at once. The new scheme is named VSPIHT (Vector SPIHT). Coding results are presented to demonstrate that the vector-based approach (without arithmetic coding) surpasses the scalar counterpart (also without arithmetic coding), in the mean-squared-error sense, for most images at low bitrates. The superiority of the vector-based approach is more pronounced for images that are generally regarded as difficult to code (such as Barbara) because of a large amount of detail.
[PDF] [BibTex]
Debargha Mukherjee and Sanjit K. Mitra,
IEEE International Symposium on Circuits and Systems, vol. 4, pp. 25-28, Monterey, California, Jun. 1998.
Node ID: 277 , DB ID: 73 , Lab: IPL , Target: Proceedings
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