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A hybrid SAR image registration algorithm base on SURF and mutual information

机译:冲浪和互信息的混合SAR图像配准算法

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摘要

Aim at the problems of features points is difficult to extract, image deformation is difficult to estimate and low registration accuracy in synthetic aperture radar (SAR) image. This paper present a hybrid SAR image registration algorithm base on speeded up robust features (SURF) and mutual information. The hybrid registration algorithm consists of coarse registration and fine registration, respectively. In the coarse registration stage, use SURF algorithm finds the regional extreme value feature points, due to the SURF algorithm ignore structural features, we use Harris corner detection algorithm to extract corner feature, thus extend the feature points to improve the accuracy of coarse registration. Acquire image transform parameters by affine transformation model. In the fine registration stage, through maximize mutual information (MI) to complete the further registration, acquire the more accuracy of image transform parameters, and achieve the high accuracy SAR image registration. The experimental results shows that the method presented in this paper can improve the accuracy of the algorithm.
机译:目的在特征点的问题难以提取,图像变形难以估计和合成孔径雷达(SAR)图像中的低登记精度。本文在加速强大的鲁棒特征(冲浪)和相互信息上存在一个混合SAR图像配准算法。混合注册算法分别由粗略注册和精细配准。在粗略登记阶段,使用SURF算法找到区域极值特征点,由于冲浪算法忽略了结构特征,我们使用HARRIS角检测算法提取拐角功能,从而扩展特征点以提高粗略配准的准确性。通过仿射变换模型获取图像变换参数。在精细登记阶段,通过最大化互信息(MI)来完成进一步的注册,获取图像变换参数的更准确度,实现高精度SAR图像配准。实验结果表明,本文呈现的方法可以提高算法的准确性。

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