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Article
Rate-distortion adaptive vector quantization for wavelet imagecoding
2000 IEEE International Conference on Acoustics, Speech, and Signal Processing
  • Qun Gu, Utah State University
  • Scott E. Budge, Utah State University
Document Type
Article
Publisher
IEEE
Location
Istanbul
Publication Date
6-1-2000
DOI
10.1109/ICASSP.2000.859200
Abstract

We propose a wavelet image coding scheme using rate-distortion adaptive tree-structured residual vector quantization. Wavelet transform coefficient coding is based on the pyramid hierarchy (zero-tree), but rather than determining the zero-tree relation from the coarsest subband to the finest by hard thresholding, the prediction in our scheme is achieved by rate-distortion optimization with adaptive vector quantization on the wavelet coefficients from the finest subband to the coarsest. The proposed method involves only integer operations and can be implemented with very low computational complexity. The preliminary experiments have shown some encouraging results: a PSNR of 30.93 dB is obtained at 0.174 bpp on the test image LENA (512×512)

Citation Information
Qun Gu and S. E. Budge, "Rate-distortion adaptive vector quantization for wavelet image coding," 2000 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.00CH37100), Istanbul, 2000, pp. 1903-1906 vol.4.