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资源三号卫星影像超分辨率重建 被引量：2

Super Resolution Reconstruction of ZY-3 Satellite Images
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摘要 研究了迭代反投影重建的方法与基于稀疏表示和字典学习的重建方法,将两种重建算法首次用于资源三号三线阵影像数据的重建试验,并从亮度均值、峰值信噪比、信息熵和清晰度等四方面对实验结果进行客观分析.重建影像结果表明:基于字典学习和稀疏表示的重建方法获得的资源三号重建影像效果优于迭代反投影方法. Two refactoring approaches, one based on iterative back projection （IBP） and the other based on sparse representation and dictionary learning, are discussed. Three linear array images of the ZY-3 satellite are used to reconstruct super-resolution images. The reconstruction results are evaluated according to four objective criteria, i.e., mean brightness, PSNR, information entropy, and sharpness of images. The results obtained with the two approaches show that the sparse representation and dictionary learning method is better than the iterative back projection method.
作者 贾永红 吕臻 周明婷
机构地区 武汉大学遥感信息工程学院 武汉大学测绘遥感信息工程国家重点实验室
出处 《应用科学学报》 CAS CSCD 北大核心 2015年第3期309-316,共8页 Journal of Applied Sciences
基金 国家科技支撑计划课题基金(No.2011BAB01B05)资助
关键词 超分辨率 特征匹配 迭代反投影 字典学习 稀疏表示 super-resolution, feature matching, iterative back projection （IBP）, dictionarylearning, sparse representation
分类号 P237.3 [天文地球—摄影测量与遥感]
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参考文献23

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二级参考文献43

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