An effecive night video enhancement algorithm
Yunbo Rao, Zhongho Chen, Ming–Ting Sun, Yu-Feng Hsu, Zhengyou Zhang · 2011
Night video enhancement is important for video surveillance since many objects or activities of interest occur in a dark environment which cannot be seen easily without enhancement. In this paper, we discuss several problems of existing techniques for illumination-fusion based night video enhancement, which fuses video frames from day-time backgrounds and night-time video. We then present a simple enhancement algorithm without these problems. The algorithm uses an additive enhancement term with foreground object extraction and constrained low-passed object illumination to avoid light-inversion and sensitivity problems and to reduce ghost patterns. Experimental results show the effectiveness and robustness of the proposed algorithm.