Single hazy image restoration using robust atmospheric scattering model

Abstract

Images captured in unfavorable weather usually exhibit poor visibility, which results from scattering and absorption that the propagated light suffers in the atmosphere. To improve the quality of degraded images, multitudes of algorithms have been exploited based on traditional atmospheric scattering model. However, in the traditional model, a phenomenon is neglected that the radiance projected on scenes is uneven, which leads to low brightness in processed image. Targeted the inherent limitation of the traditional model, we propose a robust atmospheric scattering model by decomposing the real scene into incident light and reflectance component and attaching a noise term in the traditional model. Then an objective function which includes novel regularization terms for the incident light and reflectance is formulated based on the proposed model, and an alternating direction method of multipliers is adopted to jointly estimate the incident light and reflectance. Moreover, a compensation term with regard to transmission map is introduced to ameliorate over-enhancement in thick haze regions. Ultimately, comprehensive tests are implemented to compare our method with other exceptional haze removal methods. Experiments on images with different characteristics manifest excellent performance of the proposed method in terms of haze removal and brightness enhancement.