Open AccessScene‐adaptive single image dehazing via opening dark channel model
Author(s) -
Liu Xin,
Zhang He,
Tang Yuan Yan,
Du JiXiang
Publication year - 2016
Publication title -
iet image processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.401
H-Index - 45
eISSN - 1751-9667
pISSN - 1751-9659
DOI - 10.1049/iet-ipr.2016.0138
Subject(s) - visibility , computer science , haze , channel (broadcasting) , computer vision , artificial intelligence , distortion (music) , image restoration , filter (signal processing) , image (mathematics) , fidelity , transmission (telecommunications) , halo , image processing , optics , physics , telecommunications , amplifier , bandwidth (computing) , quantum mechanics , galaxy , meteorology
Many traditional dark channel prior based haze removal schemes often suffer from the colour distortion and generate halo artefacts in the remote scenes. To tackle these issues, the authors present an efficient scene‐adaptive single image dehazing approach via opening dark channel model (ODCM). First, the authors detect the image depth information and separate it into close view and distant view. Then, an ODCM is proposed to optimise the whole atmospheric veil, in which the values of close view are regularised by a minimum channel image while the distant parts are estimated by an appropriate lower constant. Accordingly, the transmission map can be further optimised by guide filter and smoothed by domain transform filter. Finally, the haze degraded image can be well restored by the atmosphere scattering model. The extensive experiments have shown that the proposed image dehazing approach has significantly increased the perceptual visibility of the scene and achieved a better colour fidelity visually.