Nighttime low illumination image enhancement with single image using bright/dark channel prior [PDF]
EURASIP Journal on Image and Video Processing, 2018 Nighttime low illumination image enhancement is highly desired for outdoor computer vision applications. However, few works have been studied towards this goal. In addition, the low illumination enhancement problem becomes very challenging when the depth
Zhenghao Shi +4 more
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Low-light image restoration using bright channel prior-based variational Retinex model [PDF]
EURASIP Journal on Image and Video Processing, 2017 This paper presents a low-light image restoration method based on the variational Retinex model using the bright channel prior (BCP) and total-variation minimization.
Seonhee Park +4 more
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Underwater low-light enhancement network based on bright channel prior and attention mechanism. [PDF]
PLoS ONE, 2023 At present, there are some problems in underwater low light image, such as low contrast, blurred details, color distortion. In the process of low illumination image enhancement, there are often problems such as artifacts, loss of edge details and noise ...
Zhangjing Zheng, Xixia Huang, Le Wang
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Haze Level Evaluation Using Dark and Bright Channel Prior Information
Atmosphere, 2022 Haze level evaluation is highly desired in outdoor scene monitoring applications. However, there are relatively few approaches available in this area. In this paper, a novel haze level evaluation strategy for real-world outdoor scenes is presented.
Ying Chu, Fan Chen, Hong Fu, Hengyong Yu
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A low‐light image enhancement method based on bright channel prior and maximum colour channel [PDF]
IET Image Processing, 2021 Low‐light image enhancement algorithms have been introduced to improve the visual quality of low‐light images that may degrade the performance of many computer vision and multimedia systems designed for high‐quality images.
Ghada Sandoub +3 more
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Single-Image Dehazing Using Extreme Reflectance Channel Prior
IEEE Access, 2021 Image dehazing algorithms based on dark channel prior principle have achieved good results for most scenes. However, the popular dark channel prior tends to underestimate transmissions of bright areas or objects, such as the skies, white areas and self ...
Yutong Zhang +6 more
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Single image dehazing based on bright channel prior model and saliency analysis strategy [PDF]
IET Image Processing, 2021 Haze is a common atmospheric phenomenon that causes poor visibility in outdoor images, which greatly limits image application in later stages. Therefore, haze removal has become the first and most indispensable step when dealing with degraded images.
Libao Zhang, Shan Wang, Xiaohan Wang
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Region Adaptive Single Image Dehazing
Entropy, 2021 Image haze removal is essential in preprocessing for computer vision applications because outdoor images taken in adverse weather conditions such as fog or snow have poor visibility.
Changwon Kim
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Image Haze Removal Algorithm Using a Logarithmic Guide Filtering and Multi-Channel Prior
IEEE Access, 2021 In reality, the quality of an image is generally affected by haze. To obtain a well-quality image, removing haze is a hot issue on theory and application. This paper proposes a new algorithm to remove haze of hazy images.
Yuanyang Zou +3 more
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Blind Image Deblurring via a Novel Sparse Channel Prior
Mathematics, 2022 Blind image deblurring (BID) is a long-standing challenging problem in low-level image processing. To achieve visually pleasing results, it is of utmost importance to select good image priors. In this work, we develop the ratio of the dark channel prior (
Dayi Yang, Xiaojun Wu, Hefeng Yin
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