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

Author

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  • Hai-jiao Yun
  • Zhi-yong Wu
  • Guan-jun Wang
  • Gang Tong
  • Hua Yang

Abstract

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.

Suggested Citation

  • Hai-jiao Yun & Zhi-yong Wu & Guan-jun Wang & Gang Tong & Hua Yang, 2016. "A Novel Enhancement Algorithm Combined with Improved Fuzzy Set Theory for Low Illumination Images," Mathematical Problems in Engineering, Hindawi, vol. 2016, pages 1-9, May.
    • Handle: RePEc:hin:jnlmpe:8598917
    DOI: 10.1155/2016/8598917
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