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Accurate multi-spectral image registration based on scale invariant feature

机译:基于尺度不变特征的精确多光谱图像配准

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Aim at automatic registration of temporal images, multispectral images and multisensor images with rigid affine displacement, a new registration algorithm based on scale invariant local feature matching is presented in this paper. The proposed method build optimized local feature descriptors according to the character of remote sensing images and obtain the correct set of corresponding points while minimizing the points set feature distance on the basis of the relative main orientation and scale ratio; muliti-data sample consensus algorithm is adopted to attain final registration while the coordinates of the corners are further refined. Experimental results confirm that the correct rate and registration accuracy are substantially improved by the proposed algorithm.
机译:针对具有刚性仿射位移的时间图像,多光谱图像和多传感器图像的自动配准,提出了一种基于尺度不变局部特征匹配的新配准算法。该方法根据遥感图像的特征建立了优化的局部特征量,并在根据相对主要方向和比例尺使点集特征距离最小的同时,获得了正确的对应点集。采用多数据样本共识算法进行最终配准,同时进一步细化角点的坐标。实验结果证明,该算法大大提高了正确率和配准精度。

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