陈行, 罗斌. 利用动态上采样滤波深度网络进行多角度遥感影像超分辨率重建[J]. 武汉大学学报 ( 信息科学版), 2021, 46(11): 1716-1726. DOI: 10.13203/j.whugis20200651
引用本文: 陈行, 罗斌. 利用动态上采样滤波深度网络进行多角度遥感影像超分辨率重建[J]. 武汉大学学报 ( 信息科学版), 2021, 46(11): 1716-1726. DOI: 10.13203/j.whugis20200651
CHEN Hang, LUO Bin. Multi-angle Remote Sensing Images Super-Resolution Reconstruction Using Dynamic Upsampling Filter Deep Network[J]. Geomatics and Information Science of Wuhan University, 2021, 46(11): 1716-1726. DOI: 10.13203/j.whugis20200651
Citation: CHEN Hang, LUO Bin. Multi-angle Remote Sensing Images Super-Resolution Reconstruction Using Dynamic Upsampling Filter Deep Network[J]. Geomatics and Information Science of Wuhan University, 2021, 46(11): 1716-1726. DOI: 10.13203/j.whugis20200651

利用动态上采样滤波深度网络进行多角度遥感影像超分辨率重建

Multi-angle Remote Sensing Images Super-Resolution Reconstruction Using Dynamic Upsampling Filter Deep Network

  • 摘要: 近年来,基于深度学习的超分辨率重建技术已经广泛应用于多时相高光谱影像、高分影像超分辨率重建等领域。多角度遥感影像之间具有丰富的互补信息,可用于超分辨率重建。针对高分辨率多角度遥感影像提出了一种基于动态上采样滤波网络的超分辨率重建方法。该方法的网络结构为端到端双路网络,其中一个分支网络通过动态上采样滤波模块来实现分辨率提升,另一个分支网络用来学习影像中的高频信息,将两个分支网络输出的结果相加即可得到最终的超分辨率重建影像。为了验证该方法的有效性,利用WorldView-2美国亚特兰大地区和巴西里约热内卢地区多角度遥感影像数据分别进行了2倍、3倍、4倍超分辨率重建模拟实验和真实实验,并进行了多组对比实验。实验结果表明,所提方法可以在顾及多角度影像角度维信息的同时有效提升目标影像空间分辨率,并且较好地保持了影像的细节信息。

     

    Abstract:
      Objectives  Deep learning based on super-resolution reconstruction technology has been widely used in multi-temporal hyperspectral images, high-resolution image reconstruction. Multi-angle remote sensing images have rich complementary information, which is suitable for super-resolution reconstruction.
      Methods  An end-to-end super-resolution reconstruction method based on dynamic upsampling filter network is proposed for high-resolution multi-angle remote sensing images. The network of the method includes an end-to-end two-way network, in which one branch is used dynamic upsampling filter block to improve the image resolution. Another branch network is used to learn the high-frequency information in the image. In order to verify the effectiveness of the proposed method, 2, 3 and 4 times super-resolution reconstruction simulation experiments and real experiments are carried out with Worldview-2 multi-angle remote sensing images from Atlanta, America and Rio de Janeiro, Brazil, respectively. Several groups of comparative experiments are carried out.
      Results and Conclusions  Experimental results show that the proposed method can effectively improve the spatial resolution of the target image while taking into account the angle dimension information of multi angle images, and effectively maintain the image details.

     

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