最优方向耦合字典学习的遥感影像超分辨率重建-计算机工程与应用.pdf

Computer Engineering and Applications 计算机工程与应用 2018 ，54（7 ） 201 最优方向耦合字典学习的遥感影像超分辨率重建 用 1 1，2 3 1 王 雪 ，隋立春 ，杨振胤 ，康军梅 应 1 1, 2 3 1 WANG Xue , SUI Lichun , YANG Zhenyin , KANG Junmei 与 1.长安大学 地质工程与测绘学院，西安 710054 程 2.地理国情监测国家测绘地理信息局 工程技术研究中心，西安 710054 g 3. 中国电建集团 西北勘测设计研究院有限公司，西安 710065 r 工 o 1.College of Geology Engineering and Geomatics, Chang ’an University, Xi ’an 710054, China . j 2.Engineering Research Center, Geographical Conditions Monitoring National Administration of Surveying, Mapping and 机 a Geoinformation, Xi ’an 710054, China e 算 3.Northwest Engineering Corporation Limited, POWERCHINA, Xi ’an 710065, China c 计 w. WANG Xue, SUI Lichun, YANG Zhenyin, et al. Super- resolution reconstruction algorithm of remote sensing images based on method of optimal directions to coupled dictionary learning. Computer Engineering and Applica- w tions, 2018, 54 （7 ）：201-205. w 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 sample