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codewords distribution-Based Optimal Combination of Equal-Average Equal-Variance Equal-Norm Nearest Neighbor Fast Search Algorithm for Vector Quantization Encoding

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IEEE TRANSACTIONS ON IMAGE PROCESSING 2016年第12期25卷 5806-5813页

作者： Xie, Yong-Fang Liu, Jian-Hua Zhang, Chang-Fan Kong, Ling-Shuang Yi, Ji-Liang Cent S Univ Sch Informat Sci & Engn Changsha 410083 Hunan Peoples R China Hunan Univ Technol Coll Elect & Informat Engn Zhuzhou 412007 Peoples R China

Vector quantization encoding requires expensive time to find the closest codeword through the codebook for each input vector. A fast search algorithm for encoding is proposed in this paper. The multilevel elimination criterion is still derived from the three features (mean, variance, and norm) inequalities constraints, but the order of the three inequalities constraints, instead of the predefined order like other conventional multilevel elimination criterion, is optimized to speed up the encoding procedure. In the proposed algorithm, the elimination criterion at the first level is set to mean inequality constraint because of its narrower search width, and the priority order at the second and/ or third level of variance and norm inequalities constraints is optimized based on the codewords distribution and the location of input vector in terms of the considered features. The experimental results demonstrate the effectiveness of the proposed algorithm.

关键词： Fast encoding codewords distribution vector quantization

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Performance Re-Evaluation on "codewords distribution-Based Optimal Combination of Equal-Average Equal-Variance Equal-Norm Nearest Neighbor Fast Search Algorithm for Vector Quantization Encoding"

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IEEE TRANSACTIONS ON IMAGE PROCESSING 2018年第2期27卷 718-720页

作者： Wang, Yang Pan, Zhibin Li, Rui Xi An Jiao Tong Univ Sch Elect & Informat Engn Xian 710049 Shaanxi Peoples R China

In the re-evaluated paper, Xie et al. proposed a new fast search algorithm for vector quantization encoding, which optimized the priority checking order of variance and norm inequality in order to speed up the encoding procedure. CPU time of different encoding algorithms is given to support their algorithm. However, first, some of the experimental data in the re-evaluated paper are unreasonable and unrepeatable. And second, as an improved algorithm of equal-average equal-variance equal-norm nearest neighbor fast search algorithm, the re-evaluated algorithm in fact cannot achieve a better performance than the existing improved equal-average equal-variance nearest neighbor fast search algorithm. In this paper, these two problems are analyzed, re-evaluated, and discussed in detail.

关键词： Vector quantization codewords distribution fast search algorithm priority checking order

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