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Generative adversarial network for low‐light image enhancement [PDF]
IET Image Processing, 2021 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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Unsupervised Low-Light Image Enhancement in the Fourier Transform Domain
Applied Sciences, 2023 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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Low-Light Hyperspectral Image Enhancement
IEEE Transactions on Geoscience and Remote Sensing, 2022 Due to inadequate energy captured by the hyperspectral camera sensor in poor illumination conditions, low-light hyperspectral images (HSIs) usually suffer from low visibility, spectral distortion, and various noises. A range of HSI restoration methods have been developed, yet their effectiveness in enhancing low-light HSIs is constrained.
Xuelong Li 0001 +2 more
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DCTE-LLIE: A Dual Color-and-Texture-Enhancement-Based Method for Low-Light Image Enhancement
ComputersThe enhancement of images captured under low-light conditions plays a vitally important role in the area of image processing and can significantly affect the performance of following operations.
Hua Wang +3 more
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Applied Sciences, 2023 Insufficient light, uneven light, backlighting, and other problems lead to poor visibility of the image of an electric power operation site. Most of the current methods directly enhance the low-light image while ignoring local strong light that may ...
Yang Xi, Zihao Zhang, Wenjing Wang
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Pre‐trained low‐light image enhancement transformer
IET Image ProcessingLow‐light image enhancement is a longstanding challenge in low‐level vision, as images captured in low‐light conditions often suffer from significant aesthetic quality flaws.
Jingyao Zhang, Shijie Hao, Yuan Rao
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MAGAN: Unsupervised Low-Light Image Enhancement Guided by Mixed-Attention [PDF]
Big Data Mining and Analytics, 2022 Most learning-based low-light image enhancement methods typically suffer from two problems. First, they require a large amount of paired data for training, which are difficult to acquire in most cases.
Renjun Wang +4 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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A Survey of Low-Light Image Enhancement
Proceedings of the 2022 5th International Conference on Artificial Intelligence and Pattern Recognition, 2022 With the higher requirements of computer vision image enhancement of low-light image has become an important research content of computer vision. Traditional low-light image enhancement algorithms can improve image brightness and detailed visibility to varying degrees, but due to their strict mathematical derivation, such methods have bottlenecks and ...
Weiqiang Liu +3 more
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Hierarchical guided network for low‐light image enhancement
IET Image Processing, 2021 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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