Results 11 to 20 of about 942 (213)
Towards Robust Low Light Image Enhancement
CoRR, 2022 In this paper, we study the problem of making brighter images from dark images found in the wild. The images are dark because they are taken in dim environments. They suffer from color shifts caused by quantization and from sensor noise. We don't know the true camera reponse function for such images and they are not RAW.
Sara Aghajanzadeh, David A. Forsyth
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Generative adversarial network for low‐light image enhancement
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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Improved Retinex-Theory-Based Low-Light Image Enhancement Algorithm
Applied Sciences, 2023 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
IET Image Processing, 2021 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
Frontiers in Marine Science, 2022 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
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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Adaptive Enhancement of Extreme Low-Light Images
, 2023 Existing methods for enhancing dark images captured in a very low-light environment assume that the intensity level of the optimal output image is known and already included in the training set. However, this assumption often does not hold, leading to output images that contain visual imperfections such as dark regions or low contrast.
Evgeny Hershkovitch Neiterman +2 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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Multi-Scale Low-Light Image Enhancement Network Based on U-Net [PDF]
Jisuanji gongcheng, 2022 Low light is a common phenomenon when shooting at night.Insufficient illumination causes serious loss of image details and reduces visual quality.The existing low-light image enhancement methods have insufficient perception and expression of features at ...
XU Chaoyue, YU Ying, HE Penghao, LI Miao, MA Yuhui
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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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