Improved adaptive vector quantization algorithm using hybrid codebook data structure

Recently, Shen et al. [IEEE Transactions on Image Processing 2003;12:283–95] presented an efficient adaptive vector quantization (AVQ) algorithm and their proposed AVQ algorithm has a better peak signal-to-noise ratio (PSNR) than that of the previous benchmark AVQ algorithm. This paper presents an i...

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Vydáno v:Real-time imaging Ročník 11; číslo 4; s. 270 - 281
Hlavní autoři: Chen, Hsiu-Niang, Chung, Kuo-Liang
Médium: Journal Article
Jazyk:angličtina
Vydáno: Oxford Elsevier Ltd 01.08.2005
Elsevier
Témata:
Applied sciences
Coding, codes
Exact sciences and technology
Image processing
Information, signal and communications theory
Sampling, quantization
Signal and communications theory
Signal processing
Telecommunications and information theory
Performance evaluation
Codebook
Adaptive algorithm
Vector quantization
Image processing
Coding
Data compression
Transaction processing
Data structure
Signal to noise ratio
ISSN:1077-2014, 1096-116X
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Shrnutí:Recently, Shen et al. [IEEE Transactions on Image Processing 2003;12:283–95] presented an efficient adaptive vector quantization (AVQ) algorithm and their proposed AVQ algorithm has a better peak signal-to-noise ratio (PSNR) than that of the previous benchmark AVQ algorithm. This paper presents an improved AVQ algorithm based on the proposed hybrid codebook data structure which consists of three codebooks—the locality codebook, the static codebook, and the history codebook. Due to easy maintenance advantage, the proposed AVQ algorithm leads to a considerable computation-saving effect while preserving the similar PSNR performance as in the previous AVQ algorithm by Shen et al. [IEEE Transactions on Image Processing 2003;12:283–95]. Experimental results show that the proposed AVQ algorithm over the previous AVQ algorithm has about 75% encoding time improvement ratio while both algorithms have the similar PSNR performance.
ISSN:1077-2014
1096-116X
DOI:10.1016/j.rti.2005.04.004