Boosting Diffusion Networks with Deep External Context-Aware Encoders for Low-Light Image Enhancement. [PDF]
Tang P, Wang Y, Men A.
europepmc +1 more source
FPGA-based low-light image enhancement using Retinex algorithm and coarse-grained reconfigurable architecture. [PDF]
Munaf S, Bharathi A, Jayanthi AN.
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Enhancing Underwater Images of a Bionic Horseshoe Crab Robot Using an Artificial Lateral Inhibition Network. [PDF]
Ma Y, Zheng L, Piao Y, Wang Y, Yu H.
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External defect detection of Orah mandarin based on a non-brightness correction algorithm. [PDF]
Li P, Jiang X, Wu Y, Fu Q, Qin S.
europepmc +1 more source
UAV-Based Oil Leakage Spot Detection Under Complex Illumination via a Collaborative Low-Light Enhancement and Detection Framework. [PDF]
Ha Y, Zhao L, Zhang H.
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Adaptive fusion based deep learning framework for restoring underwater image quality using multi scale attention features. [PDF]
Veeramakali T, Sayeed MS, Yogarayan S.
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SwinLightGAN a study of low-light image enhancement algorithms using depth residuals and transformer techniques. [PDF]
He M +6 more
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Reconstructing illusory camouflage patterns on moth wings using computer vision. [PDF]
Jospin LV +4 more
europepmc +1 more source
CDFFusion: A Color-Deviation-Free Fusion Network for Nighttime Infrared and Visible Images. [PDF]
Chen H, Zhang T, Zhai S, Tong X, Zhu R.
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The Retinex algorithms find wide applications as image enhancers, for their capability of preserving edges, while at the same time attenuating smooth gradients and chromatic dominants. They are characterized by the fact that the output chromatic intensity of a pixel is not determined in isolation (or looking only at the contiguous pixels) but through ...
Pezzoni, Claudio +3 more
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