快速矢量量化算法

S. Arya, D. Mount
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引用次数: 181

摘要

本文表明,如果愿意放宽寻找真正最近邻的要求,就有可能在运行时间上取得显著的改进,而矢量量化器的性能损失很小。作者提出了三种最近邻搜索算法:标准和优先k-d树搜索算法和邻域图搜索算法,其中对点集和相邻点连接的边构造有向图。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Algorithms for fast vector quantization
This paper shows that if one is willing to relax the requirement of finding the true nearest neighbor, it is possible to achieve significant improvements in running time and at only a very small loss in the performance of the vector quantizer. The authors present three algorithms for nearest neighbor searching: standard and priority k-d tree search algorithms and a neighborhood graph search algorithm in which a directed graph is constructed for the point set and edges join neighboring points.<>
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