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【百家大讲堂】基于遥感应用的图像融合技术概述

编辑: 研究生院 发布日期: 2018-08-17 浏览量:

  讲座题目:基于遥感应用的图像融合技术概述

                            Concept of Image Fusion in Remote Sensing Applications

  主 讲 人:Nicolas H. Younan

         美国密西西比州立大学教授,密西西比州立大学电子与计算机系主任

  时   间:2018年8月21日 10:00

  地   点:中关村校区 信息科学实验楼202报告厅

  主办单位:研究生院、信息与电子学院

  报名方式:扫描下方二维码

 【主讲人简介】

 

  Nicolas H. Younan 是密西西比州立大学电子与计算机系的系主任和James Worth Bagley主席。他分别于 1982年1984年从密西西比州立大学获得本科和硕士学位,1988年从俄亥俄大学获得博士学位。他的主要研究 方向包括信号处理和模式识别,尤其是在遥感图像处理应用,图像融合,特征提取和分类,自动目标识别以 及数据挖掘。他发表200余篇期刊和会议论文,他是美国IEEE协会的高级会员和IEEE GRSS协会的会员。作为 以下两个技术委员会委员:图像分析和数据融合,地球信息科学。他同时也是国际遥感模式识别协会副主席。

   Nicolas H. Younan is currently the Department Head and James Worth Bagley Chair of Electrical and Computer Engineering at Mississippi State University (MSU) . He received the B.S. and M.S. degrees from MSU in 1982 and 1984, respectively, and the Ph.D. degree from Ohio University in 1988. His research interests include signal processing and pattern recognition. He has been involved in the development of advanced image processing and pattern recognition techniques for remote sensing applications, image/data fusion, feature extraction and classification, automatic target recognition/identification, and image information/data mining. He has published over 200 papers in refereed journals and conference proceedings. He is a senior member of IEEE and a member of the IEEE Geoscience and Remote Sensing society, serving on two technical committees: Image Analysis and Data Fusion and Earth Science Informatics. He also served as the Vice Chair of the International Association on Pattern Recognition (IAPR) Technical Committee 7 on Remote Sensing.

【讲座摘要】

       对地观测卫星提供遥感数据具有丰富的空间,光谱和时序特征。为了更加充分利用这些信息,很多图像融合 的方法已经被提出。图像融合主要指同时利用两个甚至更多的图像去改进图像质量。融合之后的图像具有更 为丰富的信息且为改善图像分析提供帮助。比如,图像融合在分类、分割等方面可以带来比单个图像更好的 效果。本次报告主要回顾目前经典的在遥感应用中的图像融合方法。

   Earth observation satellites provide data covering different parts of the electromagnetic spectrum at different spatial, spectral, and temporal resolutions. To utilize these different types of image data effectively, a number of image fusion techniques have been developed. Image fusion is the set of methods, tools, and means of using data from two or more different images to improve the quality of the information. The fused image has rich information that will improve the performance of image analysis algorithms. This increase in quality of the information leads to better processing (ex: classification, segmentation) accuracies compared to using the information from one type of data alone. An investigation into the use of various concepts of image fusion in remote sensing applications will be presented.

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