Modified Image Dehazing Method Based on Dark Channel Prior

Abstract

Image dehazing is an important research topic in the field of image processing and computer vision. Image dehazing aims to remove haze in images and make image scenes clearer. Image dehazing based on dark channel prior is a currently popular type of methods. However, image dehazing results obtained by existing methods based on dark channel prior usually have color distortion and low brightness causing partial image details invisible. To alleviate this issue, we presented a modified method based on dark channel prior. First, the proposed method estimates the value of atmospheric light by using a quadtree algorithm, and uses the dark channel prior to pixelwisely estimate and optimize medium transmission. Second, the proposed method uses a classic atmospheric scattering model to generate an initial image dehazing result, and transforms the result from RGB (Red, Green, and Blue) color space to HSV (Hue, Saturation, and Value) color space. Finally, the proposed method conducts the CLAHE (Contrast Limited Adaptive Histogram Equalization) algorithm on the V component of the initial result, and maps the result into the RGB space to obtain final image dehazing result. Experimental results showed that the proposed method effectively alleviated color distortion and made image scenes clearer in image dehazing results.