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Proceedings Paper

VLSI architecture for the Hadamard-transform-based fast VQ encoder
Author(s): Shurong Cheng; Zhe-Ming Lu; Xiamu Niu
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Paper Abstract

Vector Quantization (VQ) is an efficient image compression technique. In this paper, a new VLSI architecture for Vector Quantization (VQ) encoding based on the Hadamard Transform (HT) domain with the partial distance search (PDS) technique is proposed. The PDS algorithm is a simple and efficient algorithm, which allows early termination of the distortion calculation between an input vector and a codeword by introducing a premature exit condition in the search process. By using a codeword elimination criterion based on MSE in the Hadamard transform, presorted codebook and nearest search method, a large number of codewords can be rejected before computing MSE while the image quality remaining unchanged compared to the full-search VQ encoder. The proposed fast codeword search algorithm can reduce computation and is easier to be implemented by VLSI technology. Experimental results demonstrate the effectiveness of the proposed VLSI architecture.

Paper Details

Date Published: 20 September 2001
PDF: 6 pages
Proc. SPIE 4555, Neural Network and Distributed Processing, (20 September 2001); doi: 10.1117/12.441687
Show Author Affiliations
Shurong Cheng, Harbin Institute of Technology (China)
Zhe-Ming Lu, Harbin Institute of Technology (China)
Xiamu Niu, Harbin Institute of Technology (China)

Published in SPIE Proceedings Vol. 4555:
Neural Network and Distributed Processing
Xubang Shen; Jianguo Liu, Editor(s)

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