Paper Title:
Infrared Electric Image Enhancement Based On Fuzzy Renyi Entropy and Quantum Genetic Algorithm
  Abstract

Infrared thermograph has been applied in electric equipment inspection widely, but the visual effects of infrared images are always undesirable. Considering the limitation of low luminance,low contrast in infrared images,an enhancement method based on fuzzy Renyi entropy and quantum genetic algorithm is presented in this paper.Firstly,the contrast-sketching function presented in [1] is improved based on the idea of segmentation. Then, in order to segment the infrared image, Renyi entropy is extend to fuzzy domain considering the fuzzy nature of infrared image, and is employed to threshold the infrared image following maximal entropy principle. In order to meet the real-time demand of online monitoring, quantum genetic algorithm is employed to search the optimal parameters of the transform function. The experimental results indicate that the method can well improve the visual effect of infrared electric images.

  Info
Periodical
Edited by
Honghua Tan
Pages
1774-1780
DOI
10.4028/www.scientific.net/AMM.66-68.1774
Citation
S. H. Fan, S. H. Yang, P. He, H. Y. Nie, "Infrared Electric Image Enhancement Based On Fuzzy Renyi Entropy and Quantum Genetic Algorithm", Applied Mechanics and Materials, Vols. 66-68, pp. 1774-1780, 2011
Online since
July 2011
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