Single Image Dehazing Based on Convolutional Neural Network Using Boundary Constraint
Author:
Publisher
Pleiades Publishing Ltd
Subject
Computer Graphics and Computer-Aided Design,Computer Vision and Pattern Recognition
Link
https://link.springer.com/content/pdf/10.1134/S1054661821040143.pdf
Reference24 articles.
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2. B. Cai, X. Xu, K. Jia, C. Qing, and D. Tao, “DehazeNet: An end-to-end system for single image haze removal,” IEEE Trans. Image Process. 25, 5187–5198, 2016. https://doi.org/10.1109/TIP.2016.2598681
3. A. Galdran, “Image dehazing by artificial multiple-exposure image fusion,” Signal Process. 149, 135–147 (2018). https://doi.org/10.1016/j.sigpro.2018.03.008
4. Y. Gao, H.-M. Hu, B. Li, Q. Guo, and S. Pu, “Detail preserved single image dehazing algorithm based on airlight refinement,” IEEE Trans. Multimedia 21, 351–362 (2019). https://doi.org/10.1109/TMM.2018.2856095
5. K. B. Gibson, D. T. Vo, and T. Q. Nguyen, “An investigation of dehazing effects on image and video coding,” IEEE Trans. Image Process. 21, 662–673, (2012). https://doi.org/10.1109/TIP.2011.2166968
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