报告题目：Decision Fusion for Urban Land Cover Classification from Hyperspectral Imagery
报告专家：Prof.Jenny Q.Du , Mississippi State University, USA
报告时间：2011年6月30日上午10:30
报告地点：遥感betway必威西汉姆联官网附三2楼多功能报告厅
Abstract
A decision fusion approach can be used to combine the results from supervised and unsupervised classifiers to improve urban land cover classification from high-resolution hyperspectral imagery. The final output of decision fusion takes advantage of the power of supervised classification in class separation and the capability of unsupervised classification in reducing spectral variation impact in homogeneous regions. A decision fusion approach can simply adopt the majority voting rule, but achieve the same objective of object-based classification. Here, we propose a weighted majority voting rule for decision fusion, where pixels in the same segment contribute differently according to their distance to the spectral centroid. The weighted majority voting rule can further improve the performance of the majority voting rule-based decision fusion.
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Dr. Du is currently an Associate Professor in the Department of Electrical and Computer Engineering at Mississippi State University. She has authored or co-authored more than 150 scientific publications including journal papers, book chapters, and peer-reviewed conference proceedings. Her research field is digital image processing and its application to remote sensing problems with an expertise on hyperspectral image exploitation. The research she has conducted covers almost all the topics in remote sensing image processing and analysis, such as target detection, anomaly detection, change detection, supervised and unsupervised classification, linear and nonlinear unmixing, endmember extraction, real-time processing, parallel processing, band selection, data compression, registration and mosaicking, sharpening, visualization, etc. Her research interests also include image super-resolution and neural networks. Dr. Du’s research has been well supported by federal agencies and local governments.
Dr. Du currently serves as the Chair of Remote Sensing and Mapping Technical Committee of International Association for Pattern Recogntion, Co-chair of Data Fusion Technical Committee of IEEE Geoscience and Remote Sensing Society (GRSS). She serves as the Guest Editor for the special issue on Spectral Unmixing of Remotely Sensed Data of IEEE Transactions on Geoscience and Remote Sensing (TGRS), the Guest Editor for the special issue on High Performance Computing in Earth Observation and Remote Sensing of IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (JSTARS), and the Guest Editor for the special issue on Exploitation of Multi-angular Data of JSTARS. She received the 2010 Best Reviewer award from IEEE GRSS.
