Image Dehazing Based on Gradient Guided Polarization Degree Estimation
In foggy or hazy weather,the scattering of light by atmospheric particles weaken the details of optical im-ages,which affects the subsequent image analysis and processing tasks seriously. The existing dehazing algorithms have problems such as the loss of image information,blurring and excessive enhancement of the sky after dehazing. Starting from the perspective of polarization and dark channel prior theory,this article proposes a target polarization degree estima-tion algorithm using the gradient feature of the direct transmission light intensity as guidance for image dehazing. The po-larization information of scene and atmosphere are obtained from polarized images. Then,guided by the gradient feature of the direct transmission light intensity which is estimated by dark channel prior algorithm,the target polarization degree is estimated. The estimated target polarization degree is converted into atmospheric light intensity,and the optimized at-mospheric light intensity is obtained after theoretical constrainting and guided filtering atmospheric light intensity,then the optimized target polarization degree and image after dehazing are solved. Qualitative experiments show that the image dehazed by the proposed algorithm has good smoothness and overcomes the problems of existing dehazing algorithms,such as low visibility,dehazing residue and excessive enhancement of the sky. Quantitative experiments show that the pro-posed algorithm neither causes the loss of image information,nor generates excessive noise or blurs. The comparison with nine representative dehazing algorithms shows that our proposed algorithm has good ability of restoring details,improving image entropy,and enhancing the degree of tonal restoration.
万方数据
维普
