by Yilin Yang & Shiyu Dong
He K, Sun J, Tang X. Single image haze removal using dark channel prior[J]. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 2011, 33(12): 2341-2353.
Run "run.m" to remove haze on example images
Use function dehaze(I) in "dehaze.m" for any input image
The parameters are defined in "dehaze.m"
Cai B, Xu X, Jia K, et al. DehazeNet: An End-to-End System for Single Image Haze Removal[J]. arXiv preprint arXiv:1601.07661, 2016.
Run "Dehaze.sh" or "dehaze.py", "dehaze.m" to remove haze on example images
The training and test patches are in folder "patches"
The training and test labels are in "TrainLabels.txt" and "TestLabels.txt"
Run "train.sh" to train DehazeNet
Run "test.py" to calculate MSE on synthesized test data
Some images for haze removal
The results of example images using Dark Channel and DehazeNet