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Proceedings Paper

An improved contrast fusion approach in gradient domain for low light level image enhancement
Author(s): Shuning Yang; Qiong Song; Xin Guo; Yuehuan Wang
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Paper Abstract

Images often suffer from low visibility under nonuniform illumination, weak luminance and backlight environment. This paper describes a novel approach to improvement the visualization of poor light conditions. Firstly, we raise the global brightness using an adaptive exponent induced function. To enhance the local detail perception, the local contrast is boosted by contrast preserving which utilizes human vision system model. To not bias from original image, we generate the contrast combined original image and global illuminance enhance output in the gradient domain. To reduce artifacts, the guided filter is employed to estimate the local mean illuminance when transform the contrast. The experimental results demonstrate that our proposed method has a pleasant visual effect and low computational complexity than the state of the arts.

Paper Details

Date Published: 14 February 2020
PDF: 7 pages
Proc. SPIE 11428, MIPPR 2019: Multispectral Image Acquisition, Processing, and Analysis, 114280M (14 February 2020); doi: 10.1117/12.2539316
Show Author Affiliations
Shuning Yang, Science and Technology on Low-Light-Level Night Vision Lab. (China)
Qiong Song, Huazhong Univ. of Science and Technology (China)
Xin Guo, Science and Technology on Low-Light-Level Night Vision Lab. (China)
Yuehuan Wang, Huazhong Univ. of Science and Technology (China)


Published in SPIE Proceedings Vol. 11428:
MIPPR 2019: Multispectral Image Acquisition, Processing, and Analysis
Xinyu Zhang; Chao Pan; Hongshi Sang, Editor(s)

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