A novel visual perception enhancement algorithm for high-speed railway in the low light condition
Guohao Lyu, Hua Huang, Hui Yin, Siwei Luo, Xinlan Jiang · 2014
With the rapid development of high-speed railway, the safety of railway becomes extremely important. Video is a direct and effective manner for monitoring railway environment, but it is easily affected by weather condition and ambient light. Therefore the security risks are hidden in the low light condition and difficult to identify. In this paper, we propose a new visual perception enhancement algorithm VPEA based on Illuminance-Reflectance Model for low light image, and it can be used to produce a clear image from the train-borne video in the low light condition. The experimental results show that VPEA has better practical effect on image enhancement, and VPEA will be used in railway safety check and railway facility inspection in the future.