计算机工程与应用2018，Vol.54Issue(7)：201-205,5.DOI:10.3778/j.issn.1002-8331.1709-0101
最优方向耦合字典学习的遥感影像超分辨率重建
Super-resolution reconstruction algorithm of remote sensing images based on method of optimal directions to coupled dictionary learning
摘要
Abstract
In order to improve the spatial resolution of remote sensing images,this paper proposes improved joint dictionary learning algorithm.Method of optimal directions is exploited as an updating dictionary algorithm to learn coupled dictionary, and introduces sparse coefficient acquired by learning low resolution dictionary into the high resolution dictionary learning space.Exploiting sparse reconstruction method eventually generates a high resolution remote sensing image.At the same time, this algorithm is optimized, and training samples are automatically intercepted. By experiments, the results show that the proposed approach can achieve better reconstruction quality than existing algorithm in the subjective evaluation criteria. It also demonstrates effectively that the method is much faster than some classic algorithms in the process of learning dictionary,the reconstructed image is more clear and texture structure is more obvious.关键词
耦合字典/最优方向法/超分辨率重建/遥感影像/稀疏表示Key words
coupled dictionary/method of optimal directions/super-resolution reconstruction/remote sensing imagery/sparse representation分类
信息技术与安全科学引用本文复制引用
王雪,隋立春,杨振胤,康军梅..最优方向耦合字典学习的遥感影像超分辨率重建[J].计算机工程与应用,2018,54(7):201-205,5.基金项目
国家自然科学基金(No.41372330) （No.41372330）
国家自然科学基金青年基金(No.41601345). （No.41601345）
