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Mathematical Problems in Engineering
Volume 2016, Article ID 8598917, 9 pages
Research Article

A Novel Enhancement Algorithm Combined with Improved Fuzzy Set Theory for Low Illumination Images

1Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China
2University of Chinese Academy of Sciences, Beijing 100049, China

Received 6 January 2016; Revised 22 March 2016; Accepted 27 April 2016

Academic Editor: Pasquale Memmolo

Copyright © 2016 Hai-jiao Yun et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


A novel enhancement method of global brightness modulation and local contrast enhancement combined with the improved fuzzy set theory is proposed for color image contrast enhancement. The proposed method consists of three stages. Firstly, putting forward nonlinear global brightness mapping model adjusts dynamic range of images for luminance component of color space. Secondly, membership function is established in stages to adjust local contrast of image details nonlinearly based on fuzzy set theory. Finally, the enhanced images are transformed from color space into color space. The experiments further show that the proposed method has the shortest processing time, the highest AIC values, and the least NIQE values among the other four conventional methods. It has excellent effect, which can enhance the global brightness and local contrast, and advance visibility of low illumination images.