Results 131 to 140 of about 6,596,130 (203)
AE-LFOG-YOLO: robust safety helmet detection via adaptive anchors and illumination invariant learning. [PDF]
Sci RepLiu S, Wang J.
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DFCNet: Dual-Stage Frequency-Domain Calibration Network for Low-Light Image Enhancement. [PDF]
J ImagingZhou H, Li J, Mao Y, Liu L, Lu Y.
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A PDE Formalization of Retinex Theory
IEEE Transactions on Image Processing, 2010In 1964 Edwin H. Land formulated the Retinex theory, the first attempt to simulate and explain how the human visual system perceives color. His theory and an extension, the "reset Retinex" were further formalized by Land and McCann. Several Retinex algorithms have been developed ever since. These color constancy algorithms modify the RGB values at each
Catalina Sbert
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Low-Light Image Enhancement Based on Retinex Theory
2023 IEEE 6th International Conference on Electronic Information and Communication Technology (ICEICT), 2023Low-light images will likely suffer from multiple issues, such as color distortion, excessive enhancement, halo artifacts, and noise amplification when their brightness is increased.
Xin Xu, Zhibin Yu
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Low illumination image enhancement based on retinex theory
Third International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023), 2023Aiming at the problem that low visible light and noise will not only reduce the visual beauty of images but also cause the loss of important information, an improved Retinex theory method is put forward to enhance low illumination images.
Lan Zhao, Youqian Guo
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Eye detection under varying illumination using the retinex theory
Neurocomputing, 2013Eye detection plays an important role in face recognition because eyes provide distinctive facial features. However, illumination effects such as heavy shadows and drastic lighting change make it difficult to detect eyes well in facial images. In this paper, we propose a novel framework for illumination invariant eye detection under varying lighting ...
Cheolkon Jung, Licheng Jiao
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Low Light Image Enhancement Based on Retinex Theory and Diffusion Model
Proceedings of the 2024 8th International Conference on Digital Signal ProcessingThis article proposes a new method Maximum Decomposition Diffusion Enhancement(MDDE) for low light image enhancement. This method combines the advantages of Retinex theory and diffusion models, making the model physically interpretable and improving the ...
Tao Chen, Dongmei Liu
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Low illumination color image enhancement based on Gabor filtering and Retinex theory
Multimedia Tools and Applications, 2021Zhiwen Wang
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Nighttime image semantic segmentation with retinex theory
Image and Vision ComputingZhichao Sun 0004 +4 more
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