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We propose a referenceless perceptual fog density prediction model based on natural scene statistics (NSS) and fog aware statistical features. The proposed model, called Fog Aware Density Evaluator (FADE), predicts the visibility of a foggy scene from a single image without reference to a corresponding fog-free image, without dependence on salient objects(More)
We propose a perceptual fog density prediction model based on natural scene statistics (NSS) and “fog aware” statistical features, which can predict the visibility in a foggy scene from a single image without reference to a corresponding fogless image, without side geographical camera information, without training on human-rated judgments, and without(More)
We propose a referenceless perceptual defog and visibility enhancement model based on multiscale “fog aware” statistical features. Our model operates on a single foggy image and uses a set of “fog aware” weight maps to improve the visibility of foggy regions. The proposed defog and visibility enhancer makes use of statistical(More)
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