Speedup of color palette indexing in self-organization of Kohonen feature map

Authors:
Kuo-Liang Chung;Yong-Huai Huang;Jyun-Pin Wang;Ming-Shao Cheng
Affiliations:
Department of Computer Science and Information Engineering, National Taiwan University of Science and Technology, No. 43, Section 4, Keelung Road, Taipei 10672, Taiwan, ROC;Institute of Computer and Communication Engineering, Department of Electronic Engineering, Jinwen University of Science and Technology, No. 99, An-Chung Road, Hsin-Tien Dist., New Taipei City 2315 ...;Department of Computer Science and Information Engineering, National Taiwan University of Science and Technology, No. 43, Section 4, Keelung Road, Taipei 10672, Taiwan, ROC and Institute of Comput ...;Department of Computer Science and Information Engineering, National Taiwan University of Science and Technology, No. 43, Section 4, Keelung Road, Taipei 10672, Taiwan, ROC and Institute of Comput ...
Venue:
Expert Systems with Applications: An International Journal
Year:
2012

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Abstract

Based on the self-organization of Kohonen feature map (SOFM), recently, Pei et al. presented an efficient color palette indexing method to construct a color table for compression. Taking the palette indexing method as a representative, this paper presents two new strategies, the pruning-based search strategy and the lookup table (LUT)-based update strategy, to speed up the learning process in the SOFM. Based on four typical testing images, experimental results illustrate that our proposed two strategies have 35% execution-time improvement ratio in average. The practical improvement ratio is very close to that in the theoretical analysis.