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A tiny facet primitive remote sensing image registration method based on SIFT key points

机译:基于SIFT关键点的小面原始遥感图像配准方法

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Multisensory remote sensing images were achieved with different sensors in different environments; it can result in the ground information difference of the same area. So the high accurate image registration has become a pivotal hotpot problem of remote sensing image fusion research. In order to solve the remote sensing image registration problem with high accurate image registration method, a tiny facet primitive image registration method based on scale invariant feature transform (SIFT) key points is presented in this paper. By introducing the conventional tiny facet primitive method, the SIFT method can rationally solve the detection problem of the registration control points (RCPs) with the key points. Empirical results show that the detection process is with higher performance. The SIFT-based tiny facet primitive method can effectively solve the detection of RCPs and it proved to be an effective method for remote sensing image fusion and high accurate image registration.
机译:在不同的环境中使用不同的传感器获得了多传感器遥感图像;可能会导致同一区域的地面信息差异。因此,高精度的图像配准已成为遥感图像融合研究的关键热点问题。为了解决高精度图像配准方法的遥感图像配准问题,提出了一种基于尺度不变特征变换(SIFT)关键点的小面原始图像配准方法。通过引入传统的小面原始方法,SIFT方法可以合理地解决具有关键点的配准控制点(RCP)的检测问题。实验结果表明,该检测过程具有较高的性能。基于SIFT的小面原始方法可以有效地解决RCP的检测问题,是一种有效的遥感图像融合和高精度图像配准的方法。

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