报告题目：How to Effectively Design Hyperspectral Target Detection Algorithms
报 告 人：Chein-I Chang(University of Maryland, Baltimore County, USA）
报告时间：2016年7月20日（周三）上午9:00
报告地点：北校区西大楼III-405
报告摘要：
This talk follows the previous talk to focus on design and development of hyperspectral target detection algorithms. Specifically, we will discuss how to effectively take advantage of target knowledge to achieve best possible performance. In doing so, we first categorize target detection into active target detection and passive target detection according to how target knowledge is acquired. With availability of different levels of target knowledge various detection algorithms can be designed. In particular, we will discuss many currently being used target detection algorithms and integrate them under the umbrella of active/passive target detection categorization.
报告人简介：
Dr. Chang has piublsihed over 150 referred publications including more than 50 journal articles in IEEE Transaction on Geoscience and Remote Sensing and has seven patents with several pending on hyperspectral image processing. He authored three books, Hyperspectral Imaging: Techniques for Spectral Detection and Classification (Kluwer Academic Publishers, 2003), Hyperspectral Data Processing: Algorithm Design and Analysis (Wiley, 2013), Real Time Hyperspectral Image Processing: Endmember Finding and Anomaly Detection (Springer, 2016) and Real-Time Recursive Hyperspectral Sample and Band Processing: Algorithm Architecture and Implementation (to be published by Springer, 2016). In addition, He edited two books, Recent Advances in Hyperspectral Signal and Image Processing (Trasworld Research Network, India, 2006) and Hyperspectral Data Exploitation: Theory and Applications (John Wiley & Sons, 2007) and co-edited with A. Plaza a book on High Performance Computing in Remote Sensing (CRC Press, 2007).
Dr. Chang has received his Ph.D. in Electrical Engineering from University of Maryland, College Park. He is a Fellow of IEEE and SPIE with contributions to hyperspectral image processing.
