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

机译:基于SIFT键点的小型基原遥感图像登记方法

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摘要

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:在不同环境中的不同传感器实现多思科遥感图像;它可能导致相同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。为了解决高准确的图像配准方法的遥感图像配准问题,本文介绍了一种基于刻度不变特征变换(SIFT)键点的微小的小型原始图像配准方法。通过引入传统的小型原始方法,SIFT方法可以合理地利用关键点解决注册控制点(RCP)的检测问题。经验结果表明,检测过程具有更高的性能。基于SIFT的微型面原子方法可以有效解决RCP的检测,并证明是遥感图像融合和高准确图像配准的有效方法。

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