Subsampled vector quantization with nonlinear estimation using neural network approach

Huifang Sun; Constantine N. Manikopoulos; Hwei P. Hsu

doi:10.1117/12.50292

1 November 1991 Subsampled vector quantization with nonlinear estimation using neural network approach

Huifang Sun, Constantine N. Manikopoulos, Hwei P. Hsu

Proceedings Volume 1605, Visual Communications and Image Processing '91: Visual Communication; (1991) https://doi.org/10.1117/12.50292
Event: Visual Communications, '91, 1991, Boston, MA, United States

Abstract

An intraframe block coding scheme which is devoted to of using interblock redundancy and reducing the block effect is proposed. The scheme is based upon a combination of a nonlinear interpolation with transform and vector quantization techniques. Interblock redundancy is removed by extracting a pixel from each block as a common seed to interpolate the rest of the pixels of the neighboring blocks. The estimation error signals are reduced by nonlinear interpolation, which often results in no further processing requirements for some blocks. This saving compensates for the cost of transmitting the overhead of the estimation parameters.

Citation Download Citation

Huifang Sun, Constantine N. Manikopoulos, and Hwei P. Hsu "Subsampled vector quantization with nonlinear estimation using neural network approach", Proc. SPIE 1605, Visual Communications and Image Processing '91: Visual Communication, (1 November 1991); https://doi.org/10.1117/12.50292

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