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Low-Light Image Enhancement with Normalizing Flow
Proceedings of the AAAI Conference on Artificial Intelligence, 2022 To enhance low-light images to normally-exposed ones is highly ill-posed, namely that the mapping relationship between them is one-to-many. Previous works based on the pixel-wise reconstruction losses and deterministic processes fail to capture the complex conditional distribution of normally exposed images, which results in improper brightness ...
Yufei Wang 0006 +5 more
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Retinex Low-Illumination Image Enhancement Algorithm Based on Light Image Estimation [PDF]
Jisuanji gongcheng, 2021 The images collected in low-illumination environment are limited in the contrast, and suffer from detail loss and noise interference.To address the problem, a Retinex-based method is proposed to improve illumination map estimation and realize low ...
HAN Mengyan, LI Liangrong, JIANG Kai
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Gradient-Based Low-Light Image Enhancement [PDF]
2019 IEEE International Conference on Consumer Electronics (ICCE), 2019 A low-light image enhancement is a highly demanded image processing technique, especially for consumer digital cameras and cameras on mobile phones. In this paper, a gradient-based low-light image enhancement algorithm is proposed. The key is to enhance the gradients of dark region, because the gradients are more sensitive for human visual system than ...
Masayuki Tanaka 0001 +2 more
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Low Light Image Enhancement Based on Multi-Scale Network Fusion
IEEE Access, 2022 At present, researchers have made great progress in the research of object detection, however, these studies mainly focus on the object detection of images under normal lighting, ignoring the target detection under low light.
Xuan Liu +8 more
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Attention-Based Network For Low-Light Image Enhancement [PDF]
2020 IEEE International Conference on Multimedia and Expo (ICME), 2020 The captured images under low light conditions often suffer insufficient brightness and notorious noise. Hence, low-light image enhancement is a key challenging task in computer vision. A variety of methods have been proposed for this task, but these methods often failed in an extreme low-light environment and amplified the underlying noise in the ...
Cheng Zhang +5 more
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SPLIE: Optimal Illumination Estimation for Structure Preserving Low-light Image Enhancement [PDF]
Port Said Engineering Research Journal, 2021 The images taken in low-light conditions often have many flaws such as, color vividness and low visibility which negatively affects the performance of many vision-based systems.
Ghada Sandoub +3 more
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Endoscopic image enhancement with noise suppression
Healthcare Technology Letters, 2018 Stereoscopic endoscopes have been used increasingly in minimally invasive surgery to visualise the organ surface and manipulate various surgical tools. However, insufficient and irregular light sources become major challenges for endoscopic surgery.
Wenyao Xia +2 more
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Channel splitting attention network for low‐light image enhancement
IET Image Processing, 2022 Low‐light enhancement is a crucial task in computer vision because of the limited dynamic range of digital imaging devices in poor lighting conditions. Images taken under low‐light conditions often suffer from insufficient brightness and severe noise. At
Bibo Lu +3 more
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DEANet: Decomposition Enhancement and Adjustment Network for Low-Light Image Enhancement
Tsinghua Science and Technology, 2023 Poor illumination greatly affects the quality of obtained images. In this paper, a novel convolutional neural network named DEANet is proposed on the basis of Retinex for low-light image enhancement.
Yonglong Jiang +4 more
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Enhancing Low-Light Images Using Infrared Encoded Images
2023 IEEE International Conference on Image Processing (ICIP), 2023 Low-light image enhancement task is essential yet challenging as it is ill-posed intrinsically. Previous arts mainly focus on the low-light images captured in the visible spectrum using pixel-wise loss, which limits the capacity of recovering the brightness, contrast, and texture details due to the small number of income photons.
Shulin Tian +5 more
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