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Registration of multitemporal GF-1 remote sensing images with weighting perspective transformation model

机译：加权透视变换模型配准多时相GF-1遥感影像

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摘要

Registration is a classical problem in the application of remote sensing images. The existing methods prefer to fit the relationship between target and source images with the same model on the whole. In fact, the geometrical relationship between two images is not always consistent, especially for the wide-field-viewed images of GaoFen-1 (GF-1) launched by the China Aerospace Science and Technology Corporation (CASC) in April 2013. Generally, The existing methods didn't take the local deformation into consideration. Towards this end, we solve the problem with three stages in this paper. Firstly, the coarse registration obtains the integral perspective transformation model of images. Secondly, the fine registration partitions image into many blocks and improves the relationship of every block with the inverse distance weighting (IDW) function. Finally, the coordinate transformation and resampling are the final step. Compared to other methods, the experiments demonstrate that the proposed algorithm is capable of generating satisfied results which are robust against deformation at local area.
机译：配准是遥感图像应用中的经典问题。现有方法更倾向于使用整体上相同的模型来拟合目标图像和源图像之间的关系。实际上，两幅图像之间的几何关系并不总是一致的，特别是对于中国航天科技集团（CASC）于2013年4月发射的高分1号（GF-1）的宽视场图像。现有方法没有考虑局部变形。为此，我们分三个阶段来解决这个问题。首先，粗配准获得了图像的整体透视变换模型。其次，精细配准将图像划分为多个块，并利用逆距离加权（IDW）功能改善每个块的关系。最后，坐标转换和重采样是最后一步。与其他方法相比，实验证明了该算法能够产生令人满意的结果，该结果对于局部区域的变形具有鲁棒性。

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