標題: An efficient nearest neighbor searching algorithm with application to LBG codebook gene ration
作者: Wu, KS
Lin, JC
交大名義發表
資訊工程學系
National Chiao Tung University
Department of Computer Science
關鍵字: nearest neighbor (NN);vector quantization (VQ);triangular inequality;reference points (RP)
公開日期: 1-Nov-1996
摘要: The nearest neighbor (NN) searching problem has wide applications. In vector quantization (VQ), both the codebook generation phase and encoding phase (using the codebook just generated) often need to use the NN search. Improper design of the searching algorithm will make the complexity quite big as vector dimensionality k or codebook size N increases. In this paper, a fast NN searching method is proposed, which can then accelerate the LEG codebook generation process for VQ design. The method successfully modifies and improves the LAESA method. Unlike LAESA, the proposed k/2 ''fixed'' points (allocated far from the data) and the origin are used as the k/2+1 reference points to reduce the searching area. The overhead in memory is only linearly proportional to N and k. The time complexity, including the overhead, is of order O(kN). According to our experiments, the proposed algorithm can reduce the time burden while the distortion remains identical to that of the full search.
URI: http://hdl.handle.net/11536/950
ISSN: 0253-3839
期刊: JOURNAL OF THE CHINESE INSTITUTE OF ENGINEERS
Volume: 19
Issue: 6
起始頁: 719
結束頁: 724
Appears in Collections:Articles