A Blurry Low-Light Image Enhancement and Deblurring Fusion Algorithm

被引:0
|
作者
Wei, Chao [1 ,2 ]
Xu, Aisheng [1 ,2 ]
Yu, Haotian [1 ,2 ]
Chen, Yanping [1 ,2 ]
Lin, Huijing [1 ,2 ]
Chen, Guannan [1 ,2 ]
机构
[1] Fujian Normal Univ, Fujian Prov Engn Technol Res Ctr Photoelect Sensi, Fuzhou 350117, Fujian, Peoples R China
[2] Fujian Normal Univ, Fujian Prov Key Lab Photon Technol, Minist Educ, Key Lab OptoElect Sci & Technol Med, Fuzhou 350007, Fujian, Peoples R China
基金
中国国家自然科学基金;
关键词
Mobile Video; Brightness Evaluation; Lightness Enhancement; Image Deblurring;
D O I
10.1117/12.2505940
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
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.
引用
收藏
页数:5
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