A dehazing algorithm using dark channel prior and contrast enhancement
Tae Ho Kil, Sang Hwa Lee, Nam Ik Cho · 2013
This paper proposes a dehazing algorithm based on dark channel prior and contrast enhancement approaches. The conventional dark channel prior method removes haze and thus restores colors of objects in the scene, but it does not consider the enhancement of image contrast. On the contrary, the image contrast method improves the local contrast of objects, but the colors are often distorted due to the over-stretching of contrast. The proposed algorithm combines the advantages of these two conventional approaches for keeping the color while dehazing. For this, an optimization function is proposed to balance between the contrast and colors distortion, where the contrast measure follows the conventional image statistics and the hue component is used to constrain the color changes. According to the experimental results, the proposed approach compensates for the disadvantages of conventional methods, and enhances contrast with less color distortion.