Open AccessSingle image dehazing via multi‐scale gradient domain contrast enhancement
Author(s) -
Mi Zetian,
Zhou Huan,
Zheng Yijun,
Wang Minghui
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.2015.0112
Subject(s) - computer science , visibility , contrast (vision) , artificial intelligence , computer vision , radiance , image (mathematics) , residual , attenuation , transmission (telecommunications) , scale (ratio) , image restoration , remote sensing , image processing , geology , optics , algorithm , geography , telecommunications , physics , cartography
Outdoor images captured under bad weathers often suffer from low visibility. In this study, a novel method is presented to improve the visibility of a single input hazy image. On the basis of the observation that degradation of a hazy image occurs both in contrast and colour, the authors method aims at compensating the contrast and colour of the image, respectively. To achieve this, they propose a multi‐scale gradient domain contrast enhancement approach that handles the different residual images rather than the entire image, and correct the attenuation of colour according to the estimated transmission. Since there is no need to recover the scene radiance by the degradation model, their method depends less on the accuracy of transmission and does not require the estimation of atmospheric light. Experiments on a variety types of hazy images show that their method yields accurate results with fine details and vivid colour, even better than other state‐of‐the‐art dehazing methods.