Multimodal Remote Sensing Image Registration Based on Image Transfer and Local Features
Multimodal Remote Sensing Image Registration Based on Image Transfer and Local Features
复制标题
基于图像传递和局部特征的多模态遥感图像配准
DOI：
10.1109/lgrs.2019.2896341
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发表时间：
2019-08-01
影响因子：
4.8
通讯作者：
Jiao, Licheng
中科院分区：
文献类型：
--
作者：
Zhang, Jun;Ma, Wenping;Jiao, Licheng
光学、光探测与测距、合成孔径雷达等多模态遥感图像由于成像原理的差异，局部区域内的灰度、纹理、景观特征等都存在差异，因此自动配准仍然是一个具有挑战性的问题。这也使得传统的图像配准方法难以获得令人满意的结果。为了实现多模态图像的配准，以获得互补信息，我们将基于深度图像类比的转移算法应用到图像配准的预处理中。它通过融合原始图像的结构和纹理信息来消除多模态遥感图像的差异。传统的基于局部特征的方法被应用到匹配的原始和生成的图像。增加了对应性并且减小了配准误差。实验表明，该方法能有效地处理多模态数据，并产生更准确的结果。该算法基于图像深层语义特征的联合，间接实现了原始图像对的匹配。它为多模态图像配准问题提供了一种新的解决方案。
Automatic registration is still a challenging problem for multimodal remote sensing images including optical, light detection and ranging, synthetic aperture radar images, and so on. Due to the differences in imaging principles, the gray value, texture, and landscape characteristic of these images are different in the local area. This also makes it difficult to obtain satisfactory results for the conventional image registration methods. In order to achieve registration of multimodal images to obtain complementary information, we apply the transfer algorithm based on a deep image analogy to the preprocessing of image registration. It eliminates the differences in multimodal remote sensing images by blending the original image structure and texture. The conventional local feature-based method is applied to match the original and generated images. Correspondences are increased and the registration error is reduced. The experiments demonstrate that our method can effectively deal with multimodal data and produce more accurate results. The algorithm is based on the joint of image deep semantic features and indirectly achieves matching of the original image pair. It provides a new solution to the problem of multimodal images registration.