A Multi-sensor Remote Sensing Image Matching Method Based on SIFT Operator and CRA Similarity Measure

Aim to the difficulty of acquisition of conjugate points from multi-source remote sensing imagery, a novel matching method based on SIFT and CRA similarity measure is proposed. Firstly, the SIFT operator is adopted to extract feature points and coarse match is performed, the approximate transformation relationship and the rotation angle between the matched images are estimated by the above matching results. Secondly, if there exists large rotation angle between the matched images, rotation compensation on the image of matching window should be carried out, and the CRA similarity measure is used to search the corresponding points. Finally, the mismatched points in each level of pyramid images are eliminated by Quadratic polynomial with RANSAC algorithm. Repeating above procedures until the original image level, it realizes the automatic and reliable matching of multi-source remote sensing imagery. The experiment of matching of multiple SAR imagery and optical remote sensing imagery is made, and the method is validated.