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In this paper, we propose an improved atmospheric scattering model (IASM) to overcome the inherent limitation of the traditional atmospheric scattering model. Based on the IASM, a fast single image dehazing algorithm is also presented. In this algorithm, by constructing a linear model between the transmission and the haze aware density feature, the transmission map can be directly estimated through a linear operation on three components: luminance, saturation and gradient. Combining the sky-relevant feature and the proposed guided energy model (GEM), we can accurately estimate the atmospheric light and scene incident light, and can further restore the scene albedo via the IASM. Finally, an accelerating framework (AF) based on the Gaussian–Laplacian pyramid is proposed to increase the computational speed. Experimental results demonstrate that the proposed algorithm outperforms most of the prevalent algorithms in terms of visual effect and computational efficiency. Besides, it is also capable of processing various types of degraded images in addition to hazy images. [ABSTRACT FROM AUTHOR]

Outdoor images captured in bad weather are prone to yield poor visibility, which is a fatal problem for most computer vision applications. The majority of existing dehazing methods rely on an atmospheric scattering model and therefore share a common limitation; that is, the model is only valid when the atmosphere is homogeneous. In this paper, we propose an improved atmospheric scattering model to overcome this inherent limitation. By adopting the proposed model, a corresponding dehazing method is also presented. In this method, we first create a haze density distribution map of a hazy image, which enables us to segment the hazy image into scenes according to the haze density similarity. Then, in order to improve the atmospheric light estimation accuracy, we define an effective weight assignment function to locate a candidate scene based on the scene segmentation results and therefore avoid most potential errors. Next, we propose a simple but powerful prior named the average saturation prior (ASP), which is a statistic of extensive high-definition outdoor images. Using this prior combined with the improved atmospheric scattering model, we can directly estimate the scene atmospheric scattering coefficient and restore the scene albedo. The experimental results verify that our model is physically valid, and the proposed method outperforms several state-of-the-art single image dehazing methods in terms of both robustness and effectiveness. [ABSTRACT FROM AUTHOR]