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【百家大講堂】第88期:基于遙感應(yīng)用的圖像融合技術(shù)概述

發(fā)布日期:2018-08-17

  講座題目:基于遙感應(yīng)用的圖像融合技術(shù)概述

                            Concept of Image Fusion in Remote Sensing Applications

  主 講 人:Nicolas H. Younan

         美國密西西比州立大學(xué)教授,密西西比州立大學(xué)電子與計(jì)算機(jī)系主任

  時(shí)   間:2018年8月21日 10:00

  地   點(diǎn):中關(guān)村校區(qū) 信息科學(xué)實(shí)驗(yàn)樓202報(bào)告廳

  主辦單位:研究生院、信息與電子學(xué)院

  報(bào)名方式:掃描下方二維碼

 【主講人簡介】

 

  Nicolas H. Younan 是密西西比州立大學(xué)電子與計(jì)算機(jī)系的系主任和James Worth Bagley主席。他分別于 1982年1984年從密西西比州立大學(xué)獲得本科和碩士學(xué)位,1988年從俄亥俄大學(xué)獲得博士學(xué)位。他的主要研究 方向包括信號(hào)處理和模式識(shí)別,尤其是在遙感圖像處理應(yīng)用,圖像融合,特征提取和分類,自動(dòng)目標(biāo)識(shí)別以 及數(shù)據(jù)挖掘。他發(fā)表200余篇期刊和會(huì)議論文,他是美國IEEE協(xié)會(huì)的高級(jí)會(huì)員和IEEE GRSS協(xié)會(huì)的會(huì)員。作為 以下兩個(gè)技術(shù)委員會(huì)委員:圖像分析和數(shù)據(jù)融合,地球信息科學(xué)。他同時(shí)也是國際遙感模式識(shí)別協(xié)會(huì)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.

【講座摘要】

       對(duì)地觀測(cè)衛(wèi)星提供遙感數(shù)據(jù)具有豐富的空間,光譜和時(shí)序特征。為了更加充分利用這些信息,很多圖像融合 的方法已經(jīng)被提出。圖像融合主要指同時(shí)利用兩個(gè)甚至更多的圖像去改進(jìn)圖像質(zhì)量。融合之后的圖像具有更 為豐富的信息且為改善圖像分析提供幫助。比如,圖像融合在分類、分割等方面可以帶來比單個(gè)圖像更好的 效果。本次報(bào)告主要回顧目前經(jīng)典的在遙感應(yīng)用中的圖像融合方法

   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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