1 April 2004 Fast vector quantization image coding by mean value predictive algorithm
Yung-Gi Wu, Kuo-Lun Fan
Author Affiliations +
Abstract
Vector quantization (VQ) is an effective technology for signal compression. In traditional VQ, most of the computation concentrates on searching the nearest codeword in the codebook for each input vector. We propose a fast VQ algorithm to reduce the encoding time. There are two main parts in our proposed algorithm. One is the preprocessing process and the other is the practical encoding process. In preprocessing, we will generate some tables that we need to employ for practical encoding. Because those tables are used for all the images, the time to generate these tables does not increase any time in the practical encoding process. On the second part, the practical encoding process, we use the tables generated previously and other techniques to speed up the encoding time. This paper provides an effective algorithm to accelerate the encoding time. The proposed algorithm demonstrates the outstanding performance in terms of time saving and arithmetic operations. Compared to a full search algorithm, it saves more than 95% searching time.
©(2004) Society of Photo-Optical Instrumentation Engineers (SPIE)
Yung-Gi Wu and Kuo-Lun Fan "Fast vector quantization image coding by mean value predictive algorithm," Journal of Electronic Imaging 13(2), (1 April 2004). https://doi.org/10.1117/1.1666877
Published: 1 April 2004
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CITATIONS
Cited by 11 scholarly publications and 2 patents.
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KEYWORDS
Computer programming

Image compression

Distortion

Quantization

Image quality

Binary data

Fluctuations and noise

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