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Fuzzy Theory Using in Image Contrast Enhancement Technology

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Abstract

In the process of image acquisition, due to different light source distributions and positions, the problem of overexposure or underexposure will be generated during imaging. Such problems are relatively weak in the detailed information of an image, and the purpose of image enhancement technology is to solve them. Based on the fuzzy problem, this study proposed adaptive parameter image contrast enhancement technology, in order to solve the problems of overexposed and underexposed images. The analysis of the characteristics of the exposure value of an image could determine its adaptive adjustment parameters. The proposed fuzzy decision-making theory was used, and its membership function was applied for re-transformation, in order to achieve image enhancement. The experimental result proved that the fuzzy theory-based adaptive parameter image enhancement algorithm can smoothly optimize image visual quality, without over-enhancing the image, can highlight the detailed information of an image, and can conform to the feeling of human vision.

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Authors and Affiliations

  1. National Chin-Yi University of Technology, Taichung, Taiwan, ROC

    Cheng-Yi Yu, Hsueh-Yi Lin & Cheng-Jian Lin

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  1. Cheng-Yi Yu
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  2. Hsueh-Yi Lin
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  3. Cheng-Jian Lin
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Correspondence to Hsueh-Yi Lin.

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Yu, CY., Lin, HY. & Lin, CJ. Fuzzy Theory Using in Image Contrast Enhancement Technology. Int. J. Fuzzy Syst. 19, 1750–1758 (2017). https://doi.org/10.1007/s40815-017-0351-9

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  • DOI: https://doi.org/10.1007/s40815-017-0351-9

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