Single Image Dehazing with Lab Analysis

Images acquired by visual framework are genuinely corrupted under cloudy and foggy climate, therefore affecting detection, tracking and recognition of images. Thus, restoring the true scene from a hazy image is of great significance. To solve this problem, this paper presents a real-time effective dehazing algorithm for hazy surveillance images. This algorithm is based on Histogram and a filtering manipulation on La*b* color channel. In the proposed algorithm, the input RGB night image is transformed into La*b* color channel then, contrast limited adaptive histogram equalization(CLAHE) and a smoothing operation is applied respectively and simultaneously on the luminosity layer" L" and the two-color channels (a* and b*) of the La*b* color space. The channels are merged back to obtain a new enhanced image, which is transformed back to RGB image. Experimental results show the effectiveness and the short computational time of the proposed algorithm