Effective visibility restoration and enhancement of air polluted images with high information fidelity

In this paper, an effective approach for dehazing and enhancing outdoor images is proposed. The dark channel prior is used to estimate a raw transmission map. This transmission map is then refined using guided image filtering under the guidance of the hazy image. For colors and details enhancement, the adaptive manifolds high-dimensional filtering is applied to the recovered scene radiance. The proposed approach is compared with other enhancement techniques and effective quality assessment methods are used for objective evaluation. The visual information fidelity (VIF) metric is used to quantify the loss of image information, since contrast overcompensation may cause information loss. The structural similarity index (SSIM) is used to quantify the degradation of structural information between the enhanced and recovered image. Other metrics including the ratio between the gradient of visible edges before and after enhancement are also computed. Experimental results show that combining guided image filtering for refining the raw transmission map, with adaptive manifolds filtering for image enhancement, produces images with improved colors, high contrast and minimum information loss.