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A Survey of Deep Learning-Based Low-Light Image Enhancement
Images captured under poor lighting conditions often suffer from low brightness, low contrast, color distortion, and noise. The function of low-light image enhancement is to improve the visual effect of such images for subsequent processing.
Zhen Tian +6 more
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Low-light Image Enhancement Model with Low Rank Approximation [PDF]
Due to the influence of low lightness,the images acquired at dim or backlight conditions tend to have poor visual quality.Retinex-based low-light enhancement models are effective in improving the scene lightness,but they are often limited in hand-ling ...
WANG Yi-han, HAO Shi-jie, HAN Xu, HONG Ri-chang
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Multi-Feature Guided Low-Light Image Enhancement
Due to the characteristics of low signal-to-noise ratio and low contrast, low-light images will have problems such as color distortion, low visibility, and accompanying noise, which will cause the accuracy of the target detection problem to drop or even ...
Hong Liang +3 more
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Low‐light image enhancement for infrared and visible image fusion
Infrared and visible image fusion (IVIF) is an essential branch of image fusion, and enhancing the visible image of IVIF can significantly improve the fusion performance. However, many existing low‐light enhancement methods are unsuitable for the visible
Yiqiao Zhou +5 more
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Generative adversarial network for low‐light image enhancement
Low‐light image enhancement is rapidly gaining research attention due to the increasing demands of extreme visual tasks in various applications. Although numerous methods exist to enhance image qualities in low light, it is still undetermined how to ...
Fei Li +2 more
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Hierarchical guided network for low‐light image enhancement
Due to insufficient illumination in low‐light conditions, the brightness and contrast of the captured images are low, which affect the processing of other computer vision tasks.
Xiaomei Feng, Jinjiang Li, Hui Fan
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Improved Retinex-Theory-Based Low-Light Image Enhancement Algorithm
Researchers working on image processing have had a hard time handling low-light images due to their low contrast, noise, and brightness. This paper presents an improved method that uses the Retinex theory to enhance low-light images, with a network model
Jiarui Wang +3 more
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Fusion‐based simultaneous estimation of reflectance and illumination for low‐light image enhancement
Low‐light image enhancement is a challenging field in image processing. Retinex‐based methods perform well for low‐light images. However, reflectance and illumination estimation is an ill‐posed problem.
Anil Singh Parihar +3 more
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Lighting the darkness in the sea: A deep learning model for underwater image enhancement
Currently, optical imaging cameras are widely used on underwater vehicles to obtain images and support numerous marine exploration tasks. Many underwater image enhancement algorithms have been proposed in the past few years to suppress backscattering ...
Yaofeng Xie +5 more
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Unsupervised Low-Light Image Enhancement in the Fourier Transform Domain
Low-light image enhancement is an important task in computer vision. Deep learning-based low-light image enhancement has made significant progress. But the current methods also face the challenge of relying on a wide variety of low-light/normal-light ...
Feng Ming, Zhihui Wei, Jun Zhang
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