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- W2883287931 abstract "Images captured in low-light conditions are prone to suffer from low visibility, which may further degrade the performance of most computational photography and computer vision applications. In this paper, we propose a low-light image degradation model derived from the atmospheric scattering model, which is simple but effective and robust. Then, we present a physically valid image prior named pure pixel ratio prior, which is a statistical regularity of extensive nature clear images. Based on the proposed model and the image prior, a corresponding low-light image enhancement method is also presented. In this method, we first segment the input image into scenes according to the brightness similarity and utilize a high-efficiency scene-based transmission estimation strategy rather than the traditional per-pixel fashion. Next, we refine the rough transmission map, by using a total variation smooth operator, and obtain the enhanced image accordingly. Experiments on a number of challenging nature low-light images verify the effectiveness and robustness of the proposed model, and the corresponding method can show its superiority over several state of the arts." @default.
- W2883287931 created "2018-08-03" @default.
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- W2883287931 date "2018-07-16" @default.
- W2883287931 modified "2023-10-17" @default.
- W2883287931 title "A Low-Light Image Enhancement Method Based on Image Degradation Model and Pure Pixel Ratio Prior" @default.
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- W2883287931 doi "https://doi.org/10.1155/2018/8178109" @default.
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