报 告 人：刘俊 副教授，东北师范大学
报告时间：10月22日（周五）13:30
报告地点：腾讯会议（ID：950 389 620）
邀 请 人：马丽艳 副研究员                
报告摘要：
Scene recovery is a fundamental imaging task for several practical applications, e.g., video surveillance and autonomous vehicles, etc. To improve visual quality under different weather/imaging conditions, we propose a real-time light correction method to recover the degraded scenes in the cases of sandstorms, underwater, and haze. The heart of our work is that we propose an intensity projection strategy to estimate the transmission. This strategy is motivated by a straightforward rank-one transmission prior. The complexity of transmission estimation is O(N) where N is the size of the single image. Then we can recover the scene in real-time. Comprehensive experiments on different types of weather/imaging conditions illustrate that our method outperforms competitively several state-of-the-art imaging methods in terms of efficiency and robustness.
报告人简介:
刘俊, 东北师范大学数学与统计学学院副教授。2015年博士毕业于电子科技大学, 2014年-2015年美国加州大学洛杉矶分校（UCLA）博士交换生，分别于2017年和2018年短期访问香港浸会大学与香港中文大学，曾主持中国博士后科学基金面上项目和国家自然科学基金青年基金。研究方向为底层图像处理问题的数学建模与算法设计，相关研究工作发表在一些国际期刊与会议，如IEEE TPAMI，Neurocomputing，Journal of Scientific Computing, Applied Mathematical Modeling，Information Sciences，CVPR，ECCV，ICIP等。