利用偏振信息的雾天图像全局最优重构

针对雾、霾等强散射环境下相机拍摄图像严重退化的问题,提出了一种降低雾霾环境对图像质量影响的图像去雾重构方法。基于雾天偏振成像模型,分别估计图像每个区域的重构参数,获取全局最优的重构参数。利用偏振滤波的方法估计雾天大气散射光的偏振度分布,利用自适应亮通道方法计算无穷远处大气散射光的强度分布,从而重构出去雾图像。最后,利用偏振度的纹理信息对重构图像进行增强。该方法考虑了图像中不同位置大气杂散光参数的不一致性,对图像每一区域的重构参数分别运算,从而获得全局最优的重构参数图像。该方法还不要求图像必须包含天空区域,并且具有对灰度图像的处理效果较好的优点。

Global optimized hazed image reconstruction based onpolarization information

Aimed at the serious degradation problem of camera images under strong scattering environments of fog, haze and so on, a reconstruction method of image defogging was proposed to reduce the influence of fog and haze environment on the image quality.On the basis of the polarization imaging model, the global optimized reconstruction parameters were obtained by estimating every pixel''s parameters.Then, polarization filtering method was used to estimate the equivalent degree of polarization image of atmospheric scattering light and the auto adjusted light channel prior method was taken to calculate the distribution of atmospheric scattering light intensity.The global optimal reconstruction parameter image after defogging was obtained by the steps mentioned above.Finally, the texture information of polarization degree was used to enhance the image after defogging.The method pays attention in the inconsistencies of stray light parameters in different positions in images, and calculates every pixel''s parameters respectively, so it captures the global optimal reconstruction parameter images.Moreover, the method does not require its images to contain the sky area, and has an advantage for gray image processing.