Enhancing Low-light Images is very important for further processing such as Sign Recognition, Lane Detection, Surround View Generation and many other problems in the Advanced Driver Assistance Systems. This is also crucial for Consumer Applications such as Digital Cameras and Smart-phone Cameras. The current enhancement algorithms mostly rely on a Space-Invariant approach where the Contrast Enhancement is done on the entire image. However, the Low-light Scenario involves multiple problems including the rear view light scenario from point of View of Intelligent Vehicles. This problem of multiple light sources is not addressed in the current scenario. Hence we propose a Space-Variant approach that can restore the entire image with a piecewise model of the degradation that takes place in the low-light context.
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