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A blurry low-light image enhancement and deblurring fusion algorithm
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Paper Abstract

Due to the vagueness of mobile video shooting at night, the blurry low-light images obtained from it hindered humans from acquiring visual information and computer vision algorithms. In this paper, to lower color and lightness distortion when increasing visibility, a novel brightness mapping function based on the camera mapping model was proposed by using the chi-squared distribution. Then, the well-exposed images were obtained by using the brightness evaluation technique and the brightness mapping function. Finally, an existing image deblurring algorithm based on convolution and dark channel was employed to help deblur well-exposed images. Experiments showed that our method could achieve accurate contrast and lightness enhancement than several state-of-the-art methods and obtain decent sharp well-exposed images.

Paper Details

Date Published: 15 November 2018
PDF: 5 pages
Proc. SPIE 10964, Tenth International Conference on Information Optics and Photonics, 109643E (15 November 2018); doi: 10.1117/12.2505940
Show Author Affiliations
Chao Wei, Fujian Normal Univ. (China)
Aisheng Xu, Fujian Normal Univ. (China)
Haotian Yu, Fujian Normal Univ. (China)
Yanping Chen, Fujian Normal Univ. (China)
Huijing Lin, Fujian Normal Univ. (China)
Guannan Chen, Fujian Normal Univ. (China)


Published in SPIE Proceedings Vol. 10964:
Tenth International Conference on Information Optics and Photonics
Yue Yang, Editor(s)

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