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dc.contributor.advisor丁兴号
dc.contributor.author谢进
dc.date.accessioned2016-01-13T09:08:51Z
dc.date.available2016-01-13T09:08:51Z
dc.date.issued2013-12-16 15:29:38.0
dc.identifier.urihttps://dspace.xmu.edu.cn/handle/2288/79520
dc.description.abstract近年来,随着高空间分辨率和高谱间分辨率的卫星遥感图像在地球表面土地资源与环境等方面信息的获取中发挥着越来越重要的作用,遥感技术在军事侦察,地物目标检测和分类,环境保护和灾情监测与预报等领域的应用越来越广。然而受到物理因素等限制,目前,IKONOS,QuickBird和GeoEye等高分辨率光学卫星传感器不能同时获取既具有高空间分辨率又有高谱间分辨率的遥感数据;但通常这些卫星传感器会同时搭载一个全色(Panchromatic,PAN)通道和多个光谱(Multispectral,MS)通道,前者能在可见光范围内获取高空间分辨率但光谱分辨率较低的全色图像,后者能够获得多个波段的高谱间分辨率但低空间分...
dc.description.abstractIn recent years, As remote sensing images with both high spectral resolution and high spatial resolution are more and more useful for information acquisition of soil resources and ground environment, remote sensing technology has been more and more widely used in military reconnaissance, ground targets detection and classification, environmental protection, disaster monitoring and prediction. Howe...
dc.language.isozh_CN
dc.relation.urihttps://catalog.xmu.edu.cn/opac/openlink.php?strText=38916&doctype=ALL&strSearchType=callno
dc.source.urihttps://etd.xmu.edu.cn/detail.asp?serial=39164
dc.subject遥感图像融合
dc.subject非参数贝叶斯
dc.subject自适应字典
dc.subject压缩感知
dc.subjectPan-Sharpening
dc.subjectNonparametric Bayesian
dc.subjectAdaptive dictionary
dc.subjectCompressed sensing
dc.title基于非参数贝叶斯自适应字典的遥感图像Pan-Sharpening方法
dc.title.alternativePan-Sharpening Methods of Remote Sensing Image Based on Nonparametric Bayesian Adaptive Dictionary Learning
dc.typethesis
dc.date.replied2013-06-02
dc.description.note学位:工学硕士
dc.description.note院系专业:信息科学与技术学院_信号与信息处理
dc.description.note学号:23320101153152


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