Improved DCP-based image defogging using stereo images
Hasil Park, Jinho Park, Heegwang Kim, Joonki Paik · 2016
Image defogging has recently received attentions in many applications such as advanced drive assistance systems (ADAS) and intelligent surveillance systems to acquire a high-quality images. This paper presents a novel depth-based image defogging method using stereo images. The depth information obtained from a pair of stereo foggy images and then fuzzy C-mean (FCM) clustering is applied to reduce matching errors caused by atmospheric absorption and scattering during light propagation. The estimated depth information is used as weighting values in the dark channel prior (DCP)-in the defogging process. Experimental results show that the proposed method can successfully remove foggy components in the image without color distortion.