A Method for Intersection Traffic Image Enhancement Based on Adaptive Brightness Baseline Drift

As most enhancement methods do not consider the simultaneous relationship among images, light intensity, and shooting times, this paper proposes an enhancement algorithm for all-weather intersection traffic images based on adaptive brightness baseline drift (ABBD) according to illumination variations at different times. The algorithm establishes a brightness benchmark curve according to the changing illumination at different times, and then an adaptive brightness benchmark model is set up based on the brightness benchmark curve and the real-time brightness feedback. The proposed algorithm uses the brightness benchmark model to enhance the brightness of the image adaptively. Experimental results show the method's effectiveness for image enhancement in all-weather and different light conditions, as well as its robustness under different weather conditions.