公开(公告)号：US20200226413A1

公开(公告)日：2020-07-16

申请号：US16639046

申请日：2018-08-24

Applicant: SOUTHWEST JIAOTONG UNIVERSITY

Inventor： Yuanxin YE

IPC: G06K9/62 ,  G06K9/46

Abstract: A multimodal remote sensing image matching method and system integrate different local feature descriptors for automatic matching of multimodal remote sensing images. First, a local feature descriptor, such as the Histogram of Oriented Gradient (HOG), the local self-similarity (LSS), or the Speeded-Up Robust Feature (SURF), is extracted for each pixel of an image to form a pixel-wise feature representation map. Then, the three-dimensional Fourier transform (namely 3D FFT) is used to establish a fast matching similarity metric in a frequency domain based on the feature representation map, followed by a template matching scheme to achieve control points (CP) between images. In addition, the novel pixel-wise feature representation technique named channel features of orientated gradients (CFOG), which outperforms the pixel-wise feature representation methods based on the traditional local descriptors (e.g., HOG, LSS and SURF) in both matching performance and computational efficiency.