Deep space image registration is an important part of space exploration research. To improve the robustness and efficiency, a new method based on the geometry feature of the triangles constructed by neighbor stars is proposed. Considering the characteristics of deep space image, such as lower signal to noise ratio and less stable features, the star points in the image have been chosen as the feature points, and the geometric distribution of the surrounding stars are regarded as descriptors. Firstly, the distance between every pair of stars is calculated, and the neighborhood stars are determined by sorting distance. Then the main direction of the current star is determined by the intensity distribution of the neighborhood stars. Whole space is divided into eight quadrants by the Clockwise direction while setting the main direction as starting direction. The strongest stars in each quadrant is selected to construct the triangles which will be used as the descriptors of the current star. Finally, the matching distance between the stars is defined and calculated, and the voting matrix is established to determine the matching pairs. Experimental results show that compared with the traditional matching method, the proposed algorithm has higher efficiency and precision both in situations such as translation, rotation, noise.

Date Published: 9 August 2018
PDF: 10 pages
Proc. SPIE 10806, Tenth International Conference on Digital Image Processing (ICDIP 2018), 108062H (9 August 2018); doi: 10.1117/12.2502913

Published in SPIE Proceedings Vol. 10806:
Tenth International Conference on Digital Image Processing (ICDIP 2018)
Xudong Jiang; Jenq-Neng Hwang, Editor(s)