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Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/50859

Title: Fast-Searching Algorithm for Vector Quantization Using Projection and Triangular Inequality
Authors: Jim Z. C. Lai
Yi-Ching Liaw
Contributors: 國立臺灣海洋大學:資訊工程學系
Keywords: Vector quantization
Data compression
Computer science
Nearest neighbor searches
Date: 2004-12
Issue Date: 2018-10-29T02:20:16Z
Publisher: IEEE Trans. on Image Processing
Abstract: Abstract: In this paper, a new and fast-searching algorithm for vector quantization is presented. Two inequalities, one used for terminating the searching process and the other used to delete impossible codewords, are presented to reduce the distortion computations. Our algorithm makes use of a vector's features (mean value, edge strength, and texture strength) to reject many unlikely codewords that cannot be rejected by other available approaches. Experimental results show that our algorithm is superior to other algorithms in terms of computing time and the number of distortion calculations. Compared with available approaches, our method can reduce the computing time and the number of distortion computations significantly. Compared with the best method of reducing distortion computation, our algorithm can further reduce the number of distortion calculations by 29% to 58.4%. Compared with the best encoding algorithm for vector quantization, our approach also further reduces the computing time by 8% to 47.7%.
Relation: 13(12)
URI: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/50859
Appears in Collections:[資訊工程學系] 期刊論文

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