Reda, M., Zhao, Y., & Chan, J. C.-W. (2017). Polarization Guided Auto-Regressive Model for Depth Recovery. IEEE Photonics Journal, 9(3), 1-16. https://doi.org/10.1109/JPHOT.2017.2706748

@article{59196ebcac11458f9fadd935014375d6,
title = "Polarization Guided Auto-Regressive Model for Depth Recovery",
abstract = ": The Instant Dehaze method used polarized images to obtain a dehazed image and an estimated depth map of the scene. Haze due to atmospheric absorption and scattering causes degradation in image quality and the estimated depth. This estimated depth is misrepresented due to high degree of polarization and scene{\textquoteright}s objects directly illuminated by the sun. In this paper, a polarization guided auto-regressive model for depth recovery is presented. This proposed method restores the estimated depth map by incorporating polarized data to an adaptive auto-regressive (AR) model. First a 90-degree polarized image is used in our polarization term of AR coefficient, then the Stokes vector component S1 is used in our polarization guided depth map in the depth term of AR coefficient. The experimental results show that our method outperforms existing state-of-the-art schemes and improves conventional polarization dehazing method.",
keywords = "Polarization, depth recovery, dehaze, visualization, optical and other, scattering, Imaging",
author = "Mohamed Reda and Yongqiang Zhao and Chan, {Jonathan Cheung-Wai}",
year = "2017",
month = jun,
doi = "10.1109/JPHOT.2017.2706748",
language = "English",
volume = "9",
pages = "1--16",
journal = "IEEE Photonics Journal",
issn = "1943-0647",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
number = "3",
}