A novel feature point matching method of remote sensing images

Yuanquan Xu; Han Wang; Xubing Zhang; ShaoJun Wang

doi:10.1117/12.2204907

17 December 2015 A novel feature point matching method of remote sensing images

Yuanquan Xu, Han Wang, Xubing Zhang, ShaoJun Wang

Proceedings Volume 9811, MIPPR 2015: Multispectral Image Acquisition, Processing, and Analysis; 98110J (2015) https://doi.org/10.1117/12.2204907
Event: Ninth International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2015), 2015, Enshi, China

Abstract

The method of feature-based registration has been successful applied in registration of multi-source remote sensing images. Unfortunately, the mismatching still exists due to the complex textures, spectrum variation, nonlinear distortion and the large scale change. In this paper, we proposed a novel feature point matching method of multi-source remote sensing images. Firstly, the Fast-Hessian detector is to extract the feature points which are described by the SURF descriptor in the following step. After that, we analyze the local neighborhood structures of the feature points, and formulate point matching as an optimization problem to preserve local neighborhood structures. The shape context distances of the feature points are utilized to initialize matching probability matrix. Then relaxation labeling is adopted to update the probability matrix and refine the matching, which is aimed to maximize the value of the object function deduced based on preserving local neighborhood structures. Subsequently, the mismatching elimination method based on affine transformation and distance measurement is used to eliminate the residual mismatching points. During the abovementioned matching produce, the multi-resolution analysis method is adopted to decrease the scale difference between the multi-source remote sensing images. Also the mutual information method is utilized to match the feature points of the down sampling and the original images. The experimental results are shown that the proposed method was robust and efficient for registration of multi-source remote sensing images.

Citation Download Citation

Yuanquan Xu, Han Wang, Xubing Zhang, and ShaoJun Wang "A novel feature point matching method of remote sensing images", Proc. SPIE 9811, MIPPR 2015: Multispectral Image Acquisition, Processing, and Analysis, 98110J (17 December 2015); https://doi.org/10.1117/12.2204907

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KEYWORDS

Remote sensing

Image registration

Image resolution

Affine motion model

Distance measurement

Sensors

Nanoimprint lithography

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