Single Image Dehazing with Lab Analysis
Jehoiada Kofi Jackson, She Kun, Rapheal Akande · 2018
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