Fast encoding method for vector quantization based on sorting elements of codewords to adaptively constructing subvectors

Zhibin Pan, Koji Kotani, Tadahiro Ohmi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Vector quantization (VQ) is a popular image compression method and the encoding speed of VQ is very important to its practical applications. In a conventional encoding process of VQ, because a lot of k-dimensional (k-D) Euclidean distances must be computed so as to find out the best-match for each input vector, VQ is computationally very expensive. In order to avoid immediately computing the real Euclidean distance for a candidate codeword, IEENNS method has been proposed to reject the unlikely codeword by using the famous scalar features of the sum and the variance of a k-D vector. Furthermore, in order to improve the precision of Euclidean distance estimation so as to enhance the rejection capability, by dividing a k-D vector in half to generate two (k/2)-D subvectors and then apply IEENNS method again to each of the subvectors, a complete-version C-SIEENNS method and a simplified-version S-SIEENNS method have been reported recently as well. Apparently, how to construct the two (k/2)-D subvectors is the core problem in a subvector-based method for achieving a higher encoding performance. However, the previous works just fixedly construct their two subvectors by using the first half original vector of [1 ∼ k/2] dimensions and the second half original vector of [k/2+1 ∼ k] dimensions for simplicity. It is clear there is no guarantee that this kind of subvector construction way is optimal. Instead, this paper proposes a criterion to construct two better subvectors by letting the difference between the two partial sums approach the maximum based on adaptively analyzing the property of each codeword offline. Experimental results confirmed that by simply replacing the fixed subvectors with the adaptively constructed subvectors in S-SIEENNS method, it can further improve the search efficiency by 19.9%∼36.8%.

Original languageEnglish
Title of host publicationISCAS 2006
Subtitle of host publication2006 IEEE International Symposium on Circuits and Systems, Proceedings
Pages4687-4690
Number of pages4
Publication statusPublished - 2006 Dec 1
EventISCAS 2006: 2006 IEEE International Symposium on Circuits and Systems - Kos, Greece
Duration: 2006 May 212006 May 24

Publication series

NameProceedings - IEEE International Symposium on Circuits and Systems
ISSN (Print)0271-4310

Other

OtherISCAS 2006: 2006 IEEE International Symposium on Circuits and Systems
CountryGreece
CityKos
Period06/5/2106/5/24

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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    Pan, Z., Kotani, K., & Ohmi, T. (2006). Fast encoding method for vector quantization based on sorting elements of codewords to adaptively constructing subvectors. In ISCAS 2006: 2006 IEEE International Symposium on Circuits and Systems, Proceedings (pp. 4687-4690). [1693676] (Proceedings - IEEE International Symposium on Circuits and Systems).