Adapted type-II fuzzy algorithm for non-uniform illumination images
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Updated
Jan 19, 2024 - MATLAB
Adapted type-II fuzzy algorithm for non-uniform illumination images
Images captured in outdoor scenes can be highly degraded due to poor lighting conditions. These images can have low dynamic ranges with high noise levels that affect the overall performance of computer vision algorithms. To make computer vision algorithms robust in low-light conditions, use low-light image enhancement to improve the visibility o…
Retinex-Based Multiphase Algorithm for Low-Light Image Enhancement
Adaptive image enhancement method for correcting low-illumination images
Matlab Implementation of journal "A fusion-based enhancing method for weakly illuminated images" by XueyangFu, DeluZeng, YueHuang, YinghaoLiao, XinghaoDing, JohnPaisley, Signal Processing Journal, Elsevier, May 2016
基于Retinex模型和多尺度融合的低光照图像增强技术 Low-light image enhancement technology based on Retinex model and multi-scale fusion
Implementation of the paper, "LIME: Low-Light Image Enhancement via Illumination Map Estimation"
[ACMMM2023] "Enhancing Visibility in Nighttime Haze Images Using Guided APSF and Gradient Adaptive Convolution", https://arxiv.org/abs/2308.01738
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