网安学院邀请北京交通大学李晓龙教授做学术报告，欢迎各位老师和研究生参加。
报告人：李晓龙（北京交通大学，信息科学研究所，教授
报告题目：General expansion-shifting model for reversible data hiding: Theoretical investigation and practical algorithm
时间：2019年9月23日 19:00-20:00
地点：机电楼A座407会议室
个人简介：李晓龙教授于1999年、2002年及2006年分别获北京大学学士学位、法国巴黎综合理工大学硕士学位及法国卡尚大学数学博士学位。此外于2007年至2016年，先后在北京大学做博士后和研究员。李晓龙现任北京交通大学信息科学研究所教授。李晓龙教授的研究方向分别是图像处理和信息隐藏，承担了国家自然科学基金重点项目等前沿研究课题。发表SCI论文50余篇(其中IEEE会刊17篇，ESI高被引论文8篇)，国际会议论文50余篇。根据谷歌引文，李晓龙教授的学术成果被引用超过4500次，h因子为30。
报告简介：Reversible data hiding (RDH) is a specific data hiding technique in which both the embedded data and the original cover image can be exactly extracted from the marked image. In this paper, we present a general expansion-shifting model for RDH by introducing the so-called reversible embedding function (REF) which maps each point of Z^n to a non-empty subset of Z^n. Moreover, to guarantee the reversibility, the mapped subsets of distinct points should be disjointed to each other. With REF, RDH can be designed and the corresponding rate-distortion formulations can be established, providing an approach to optimize the embedding performance. Some examples of REF are given for a better illustration, and a preliminary theoretical investigation on REF is conducted as well. Then, optimal REF for one-dimensional histogram is investigated, and all optimal REF are derived in this case when the maximum modification to the cover pixel is limited as a small value. Finally, based on the optimal REF for one-dimensional histogram and the idea of multiple histograms modification, a practical RDH scheme is presented and it is experimental verified better than some state-of-the-art algorithms in terms of capacity-distortion performance.
