Abstract
Images/videos captured in low-light conditions often present low luminance and contrast. Although the existing algorithms can improve the subjective perception, color distortion and over-enhancement usually appear, which will disturb the subsequent intelligent analysis. Otherwise, due to high computational complexity, the existing algorithms are difficult to process a high resolution (HR) video (1280×720) in real-time. Therefore, a real-time low-light enhancement algorithm for intelligent analysis is proposed in this paper. Firstly, an enhancement model is established in RGB color space. Then, to judge the influence of light intensity, images of ColorChecker color chart are captured under a series of light conditions. Finally, the enhancement factor in the proposed model is evaluated by the captured images. Experimental results demonstrate that the proposed algorithm can significantly improve the performance of vehicle license plate localization and skin color detection compared to the existing algorithms. Furthermore, the proposed algorithm can process the HR videos at the speed of 28.3 fps on average.
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