It is difficult to identify video images with low contrast in a low-light environment, so an adaptive contrast compensation enhancement algorithm was proposed. First, the average gray of video image feature parameters in the low-light environment was extracted, then a mathematical model of human visual contrast resolution compensation based on the grayscale difference of original images was established, and the true color three-primary colors were compensated respectively by proportional integration. Second, the compensation threshold was set to linearly compensate photopic vision until full bandwidth when the compensation degree was lower than the just noticeable difference of photopic vision. Finally, the automatic optimization model of compensation proportion coefficient was established based on the subjective image quality evaluation and image feature parameters, which was embedded in DirectShow video processing system for video image adaptive enhancement. Experimental results show that the video enhancement system has good real-time performance, which can mine scotopic vision information effectively and be widely applied in different scenes.