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Matlab codes: Efficient Image Dehazing with Boundary Constraint and Contextual Regularization

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### Efficient Image Dehazing with Boundary Constraint and Contextual Regularization

Meng Gaofeng, Wang Ying, Duan Jiangyong, Xiang Shiming, Pan Chunhong

![](https://raw.githubusercontent.com/gfmeng/imagedehaze/master/images/fig.jpg)

### Abstract
Images captured in foggy weather conditions often
suffer from bad visibility. In this paper, we propose an efficient
regularization method to remove hazes from a single input
image. Our method benefits much from an exploration on the
inherent boundary constraint on the transmission function.
This constraint, combined with a weighted L1−norm based
contextual regularization, is modeled into an optimization
problem to estimate the unknown scene transmission. A quite
efficient algorithm based on variable splitting is also presented
to solve the problem. The proposed method requires only
a few general assumptions and can restore a high-quality
haze-free image with faithful colors and fine image details.
Experimental results on a variety of haze images demonstrate
the effectiveness and efficiency of the proposed method.

### Cite

```
@INPROCEEDINGS{6751186, 
  author={G. Meng and Y. Wang and J. Duan and S. Xiang and C. Pan}, 
  booktitle={IEEE International Conference on Computer Vision}, 
  title={Efficient Image Dehazing with Boundary Constraint and Contextual Regularization}, 
  year={2013}, 
  volume={}, 
  number={}, 
  pages={617-624}, 
  month={Dec},}
```

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