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29 October 2018 Low-light image enhancement via coupled dictionary learning and extreme learning machine
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Proceedings Volume 10836, 2018 International Conference on Image and Video Processing, and Artificial Intelligence; 108360J (2018) https://doi.org/10.1117/12.2514014
Event: 2018 International Conference on Image, Video Processing and Artificial Intelligence, 2018, Shanghai, China
Abstract
In this paper, a novel enhancement algorithm for low-light images captured under low illumination conditions is proposed. More concretely, we design a method firstly to synthesize low-light images as training datasets. Then preclustering is conducted to separate training data into several groups by a coupled Gaussian mixture model. For each group, we adopt a coupled dictionary learning approach to train the low-light and normal-light dictionary pair jointly, and the statistical dependency of the sparsity coefficients is captured via Extreme Learning Machine simultaneously. Besides, we use a multi-phase dictionary learning strategy to enhance the robustness of our method. Experimental results show that proposed method is superior to existing methods.
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Jie Zhang, Pucheng Zhou, and Mogen Xue "Low-light image enhancement via coupled dictionary learning and extreme learning machine", Proc. SPIE 10836, 2018 International Conference on Image and Video Processing, and Artificial Intelligence, 108360J (29 October 2018); https://doi.org/10.1117/12.2514014
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