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Proceedings Paper

Multistage Adaptive Vector Quantization With Least Squares Approximation
Author(s): H. Sun; H. Hsu; C. N. Manikopoulos
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Paper Abstract

In this paper, we propose an image coding scheme, multistage adaptive vector quantization with least sqaures approximation. In this scheme, an image of size 2n x 2n is first partitioned into 2m x 2m blocks (m<n). Each pixel in the block undergoes a normalization by subsracting the block mean and then dividing by the block deviation. The resulting values of each block are approximated by a 2 x 2 matrix with least squares method. If the error of approximation is greater than a preset threshold value, then the 2m x 2m block is further partitioned into four 2m-1 x 2m-1 - blocks, and each of those blocks is also approximated by a 2 x 2 matrix with least squares method. This procedure is continued from the top level of 2m x 2m blocks to the bottom level of 4 x 4 blocks. To achieve a more efficient transmission, the vector quantization is applied to the 4 or 8 dimensional vector set on level-by-level basis. The residual errors due to quantization at each level are fedforward and included in the next level. Thus, it is possible to reprocess at the lower levels, the information lost at the higher level. The simulation results demonstrate that very well reconstructed images can be obtained at the bit rate as low as 0.7 bits/pixel.

Paper Details

Date Published: 25 October 1988
PDF: 8 pages
Proc. SPIE 1001, Visual Communications and Image Processing '88: Third in a Series, (25 October 1988); doi: 10.1117/12.969018
Show Author Affiliations
H. Sun, Fairleigh Dickinson University (United States)
H. Hsu, Fairleigh Dickinson University (United States)
C. N. Manikopoulos, New Jersey Institute of Technology (United States)


Published in SPIE Proceedings Vol. 1001:
Visual Communications and Image Processing '88: Third in a Series
T. Russell Hsing, Editor(s)

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