Robust Airlight Estimation for Haze Removal from a Single Image
Abstract
Present methods for haze removal from a single image require the estimation of two physical quantities which, according to the commonly used atmospheric scattering model, are transmission and airlight. The visual quality of images de-hazed with such methods is highly dependent on the accuracy of estimation of the aforementioned quantities. In this paper we propose a new method for reliable airlight color estimation that could be used in digital cameras to automatically de-haze images by removing unrealistic color artifacts. The main idea of our method is based on novel statistics gathered from natural images regarding frequently occurring airlight colors. The statistics are used to introduce a minimization cost functional which has a closed form solution, and is easy to compute. We compare our approach with current methods present in literature, and show its superior robustness with both images with artificially added haze, and real hazy photos.
Cite
Text
Pedone and Heikkilä. "Robust Airlight Estimation for Haze Removal from a Single Image." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2011. doi:10.1109/CVPRW.2011.5981822Markdown
[Pedone and Heikkilä. "Robust Airlight Estimation for Haze Removal from a Single Image." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2011.](https://mlanthology.org/cvprw/2011/pedone2011cvprw-robust/) doi:10.1109/CVPRW.2011.5981822BibTeX
@inproceedings{pedone2011cvprw-robust,
title = {{Robust Airlight Estimation for Haze Removal from a Single Image}},
author = {Pedone, Matteo and Heikkilä, Janne},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
year = {2011},
pages = {90-96},
doi = {10.1109/CVPRW.2011.5981822},
url = {https://mlanthology.org/cvprw/2011/pedone2011cvprw-robust/}
}