Paper
15 November 2018 A blurry low-light image enhancement and deblurring fusion algorithm
Author Affiliations +
Proceedings Volume 10964, Tenth International Conference on Information Optics and Photonics; 109643E (2018) https://doi.org/10.1117/12.2505940
Event: Tenth International Conference on Information Optics and Photonics (CIOP 2018), 2018, Beijing, China
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.
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Chao Wei, Aisheng Xu, Haotian Yu, Yanping Chen, Huijing Lin, and Guannan Chen "A blurry low-light image enhancement and deblurring fusion algorithm", Proc. SPIE 10964, Tenth International Conference on Information Optics and Photonics, 109643E (15 November 2018); https://doi.org/10.1117/12.2505940
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KEYWORDS
Image enhancement

Cameras

Information visualization

Visual process modeling

Convolution

Image restoration

Algorithm development

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