Scene‐aware image dehazing based on sky‐segmented dark channel prior. Issue 12 (4th October 2017)

• Record Type: Journal Article
• Authors: Xiao, Jinsheng; Zhu, Li; Zhang, Yongqin; Liu, Enyu; Lei, Junfeng
• Is Part Of: IET image processing. Volume 11:Issue 12(2017)
• Page Start: 1163
• Page End: 1171
• Publication Date: 2017-10-04
• Subjects: image enhancement -- image colour analysis -- image segmentation -- sky brightness -- median filters -- image filtering; scene‐aware image dehazing -- sky‐segmented dark channel prior algorithm -- improved dehazing algorithm -- colour distortion problem -- halo effect -- dark channel prior theory -- guided filter -- sky region segmentation -- atmospheric light estimation -- median filter -- halo problem suppression -- empirically selected gamma parameter -- image lightness enhancement -- gamma correction; Image processing -- Periodicals; 621.36705
• DOI: 10.1049/iet-ipr.2017.0058
• Languages: English
• ISSNs: 1751-9659

Abstract

Abstract : An improved dehazing algorithm based on dark channel theory is proposed, in order to solve the problems of colour distortion and halo effect which still exists in dark channel prior algorithm. The dark channel prior theory may lead to colour distortion in sky region. Firstly, the guided filter is used to refine the segmentation of the sky region, and the atmospheric light is estimated accurately. Then, the median filter is used to obtain the detailed edge information. So a more clear transmission can be gotten which effectively suppress the halo problem. Finally, the gamma correction is applied to enhance image lightness with an empirically selected gamma parameter. The experimental results show that the proposed algorithm can effectively remove the haze. It can correct the colour distortion of the sky area and eliminate the halo effect at the edge of the scene.