NDLI: An improved fast encoding method for vector quantization based on memory-efficient data structure

Content Provider	IEEE Xplore Digital Library
Author	Zhibin Pan Kotani, K. Ohmi, T.
Copyright Year	2004
Description	Author affiliation: New Ind. Creation Hatchery Center, Tohoku Univ., Sendai (Zhibin Pan)
Abstract	Within the framework of vector quantization (VQ), the fast search method is a key issue because it is the time bottleneck in the VQ encoding process. To speed up VQ some very effective fast search methods that are based on using statistical features (i.e. the mean, the variance and $L_{2}$ norm) of a k-dimensional vector have already been proposed. It is rather easy to obtain the mean of an input vector online. However. in order to obtain the variance of an input vector, it needs (2k-1) additions (plusmn), k multiplications (times) and once square root (sqrt) operation on-line. Similarly, to obtain the L2 norm of an input vector, it also needs (k-l) additions (plusmn), k multiplications (times) and once square root (sqrt) operation on-line. Clearly, these operations are a rather heavy overhead in the search process. In addition, all computations in a search process must use real rather than integer value. For each codeword, three extra memories are necessary to store its features. To solve the overhead problem of computing the variance and $L_{2}$ norm of an input vector on-line and to make all computations in integer form possible, previous works proposed to use the sum and two partial sums only as features of a vector for reducing search space. But they need three extra memories as well for each codeword to store the features. In order to avoid this extra memory requirement this paper proposes a memory-efficient data structure for storing the sum, two partial sums and the original vector to further improve the previous works (Pan et al. (2002), (2003)). Meanwhile, a more efficient computation method for rejection tests is also developed. In addition, all computations can be realized in integer form. Experimental results confirmed that the proposed method outperforms the previous works
Starting Page	1119
Ending Page	1122
File Size	346604
Page Count	4
File Format	PDF
ISBN	0780386035
DOI	10.1109/ICME.2004.1394413
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2004-06-27
Publisher Place	Taiwan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Encoding Vector quantization Data structures Euclidean distance Data engineering Electronics industry Industrial electronics Electronic mail Image coding Distortion measurement
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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