An Iterative Image Dehazing Method with Polarization
This publication appears in: IEEE Transactions on Multimedia
Authors: L. Shen, Y. Zhao, Q. Peng, J. C-W Chan and S. G. Kong
Publication Date: Sep. 2018
This paper presents a joint dehazing and denoising scheme for an image taken in hazy conditions. Conventional image dehazing methods may amplify the noise depending on the distance and density of the haze. To suppress the noise and improve the dehazing performance, an imaging model is modified by adding the process of amplifying the noise in hazy conditions. This model offers a depth-chromaticity compensation regularization for transmission map and a chromaticity-depth compensation regularization for dehazing the image. The proposed iterative image dehazing method with polarization uses these two joint regularization schemes and the relationship between transmission map and dehazed image. The transmission map and irradiance image are used to promote each other. To verify the effectiveness of the algorithm, polarizing images of different scenes in different days are collected. Different algorithms are applied to the original images. Experiment results demonstrate that the proposed scheme increases visibility in extreme weather conditions without amplifying the noise.