Pansharpening for Cloud-Contaminated Very High-Resolution Remote Sensing Images
Pansharpening for Cloud-Contaminated Very High-Resolution Remote Sensing Images
复制标题
受云污染的超高分辨率遥感图像的全色锐化
DOI：
10.1109/tgrs.2018.2878007
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发表时间：
2019-05
影响因子：
8.2
通讯作者：
Sun Weiwei
中科院分区：
文献类型：
--
作者：
Meng Xiangchao;Shen Huanfeng;Yuan Qiangqiang;Li Huifang;Zhang Liangpei;Sun Weiwei
光学遥感图像不仅要在空间分辨率和光谱分辨率之间做出根本性的权衡，而且不可避免地会受到云的污染；然而，现有的全锐化方法主要集中在无云污染的光学遥感图像的分辨率增强上。如何将被云污染的图像进行融合，实现联合的分辨率增强和去云，是一项具有挑战性的工作。针对具有挑战性的云污染超高分辨率遥感图像，提出了一种全景锐化方法。此外，还综合考虑了全厚云、全薄云、全霾、全云阴影的实际观测的云污染条件。在该方法中，提出了一种基于多源和多时相观测的两步融合框架：1)首先联合去除薄云、阴霾和轻云阴影；2)提出了一种基于变分的综合融合模型，实现了厚云和暗云阴影的联合分辨率增强和缺失信息重建。通过提出的融合方法，可以获得高空间分辨率和高光谱分辨率的无云融合图像。为了全面测试和验证该方法，利用IKONOS、QuickBird、吉林(JL)1号和Deimos-2等不同遥感卫星的无云图像和有云图像进行了实验。实验结果证实了该方法的有效性。
The optical remote sensing images not only have to make a fundamental tradeoff between the spatial and spectral resolutions, but also are inevitable to be polluted by the clouds; however, the existing pansharpening methods mainly focus on the resolution enhancement of the optical remote sensing images without cloud contamination. How to fuse the cloud-contaminated images to achieve the joint resolution enhancement and cloud removal is a promising and challenging work. In this paper, a pansharpening method for the challenging cloud-contaminated very high-resolution remote sensing images is proposed. Furthermore, the cloud-contaminated conditions for the practical observations with all the thick clouds, the thin clouds, the haze, and the cloud shadows are comprehensively considered. In the proposed methods, a two-step fusion framework based on multisource and multitemporal observations is presented: 1) the thin clouds, the haze, and the light cloud shadows are proposed to be first jointly removed and 2) a variational-based integrated fusion model is then proposed to achieve the joint resolution enhancement and missing information reconstruction for the thick clouds and dark cloud shadows. Through the proposed fusion method, a promising cloud-free fused image with both high spatial and high spectral resolutions can be obtained. To comprehensively test and verify the proposed method, the experiments were implemented based on both the cloud-free and cloud-contaminated images, and a number of different remote sensing satellites including the IKONOS, the QuickBird, the Jilin (JL)-1, and the Deimos-2 images were utilized. The experimental results confirm the effectiveness of the proposed method.
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DOI：
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发表时间：
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期刊：
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影响因子：
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