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Feng Tian, Mengjiao Wang and Xiaopei Liu
Aiming at solving the problems of local halo blurring, insufficient edge detail preservation, and serious noise in traditional image enhancement algorithms, an improved Retinex algorithm for low-light mine image enhancement is proposed. Firstly, in HSV c...
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Huapeng Tang, Danyang Qin, Jiaqiang Yang, Haoze Bie, Yue Li, Yong Zhu and Lin Ma
In indoor low-light environments, the lack of light makes the captured images often suffer from quality degradation problems, including missing features in dark areas, noise interference, low brightness, and low contrast. Therefore, the feature extractio...
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Xinxin Pan, Changli Li, Zhigeng Pan, Jingwen Yan, Shiqiang Tang and Xinghui Yin
Recently, low-light image enhancement has attracted much attention. However, some problems still exist. For instance, sometimes dark regions are not fully improved, but bright regions near the light source or auxiliary light source are overexposed. To ad...
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Hao Tang, Hongyu Zhu, Huanjie Tao and Chao Xie
Due to the influence of the environment and the limit of optical equipment, low-light images produce problems such as low brightness, high noise, low contrast, and color distortion, which have a great impact on their visual perception and the following i...
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Zhaoyang Wang, Dan Zhao and Yunfeng Cao
Aiming at the problem that obstacle avoidance of unmanned aerial vehicles (UAVs) cannot effectively detect obstacles under low illumination, this research proposes an enhancement algorithm for low-light airborne images, which is based on the camera respo...
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Lijia Yu, Jie Luo, Shaoping Xu, Xiaojun Chen and Nan Xiao
Image denoising is a classic but still important issue in image processing as the denoising effect has a significant impact on subsequent image processing results, such as target recognition and edge detection. In the past few decades, various denoising ...
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