关键词: 偏振图像, HIS变换, RGB空间, 去雾模型, 暗原色先验

Abstract: Aiming at not satisfactory defogging effect of the traditional defogging algorithm based on polarized characteristics in heavy fog, a new color space conversion algorithm using dark channel prior for polarization image dehazing was proposed. Compared with the traditional imaging technology, polarization imaging detection technology has remarkable advantages in the target detection and recognition of complex environment. Intensity, polarization degree and polarization angel information are usually used to describe target's polarization information for polarization images. In order to combine the polarization information and defogging model, a method of color space transformation was adopted. Firstly, the polarization information was converted into the components of the brightness, hue, saturation in Hue-Intensity-Saturation (HIS) color space and then the HIS color space was mapped to the Red-Green-Blue (RGB) space. Secondly, the dark channel prior principle was applied to get the dark channel image with the combination of the atmospheric scattering model in haze weather. Finally, the atmospheric transmission rate was elaborated by using softmatting algorithm based on sparse prior of the image. The experimental results show that, compared with the existing polarization defogging algorithm, many technical specifications of defogged images such as standard deviation, entropy, average gradient of the proposed algorithm have been greatly improved in very low visibility conditions. The proposed algorithm can effectively enhance the global contrast in heavy fog weather and improve the identification capability for the polarized images.

Key words: polarized image, Hue-Intensity-Saturation (HIS) transform, Red-Green-Blue (RGB) space, defogging model, dark channel prior