JOURNAL ARTICLE

A blurry low-light image enhancement and deblurring fusion algorithm

Guannan ChenHuijing LinChao WeiAisheng XuHaotian YuYanping Chen

Year: 2018 Journal:   Tenth International Conference on Information Optics and Photonics Pages: 158-158

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.

Keywords:
Deblurring Artificial intelligence Computer vision Lightness Brightness Computer science Visibility Distortion (music) Convolution (computer science) Unsharp masking Image restoration Image (mathematics) Image enhancement Image processing Optics Physics Artificial neural network

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Topics

Advanced Image Processing Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Advanced Image Fusion Techniques
Physical Sciences →  Engineering →  Media Technology
Image Enhancement Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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