Share Email Print
cover

Proceedings Paper

Automatic SAR and optical images registration method based on improved SIFT
Author(s): Chunyu Yue; Wanshou Jiang
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper Abstract

An automatic SAR and optical images registration method based on improved SIFT is proposed in this paper, which is a two-step strategy, from rough to accuracy. The geometry relation of images is first constructed by the geographic information, and images are arranged based on the elevation datum plane to eliminate rotation and resolution differences. Then SIFT features extracted by the dominant direction improved SIFT from two images are matched by SSIM as similar measure according to structure information of the SIFT feature. As rotation difference is eliminated in images of flat area after rough registration, the number of correct matches and correct matching rate can be increased by altering the feature orientation assignment. And then, parallax and angle restrictions are introduced to improve the matching performance by clustering analysis in the angle and parallax domains. Mapping the original matches to the parallax feature space and rotation feature space in sequence, which are established by the custom defined parallax parameters and rotation parameters respectively. Cluster analysis is applied in the parallax feature space and rotation feature space, and the relationship between cluster parameters and matching result is analysed. Owing to the clustering feature, correct matches are retained. Finally, the perspective transform parameters for the registration are obtained by RANSAC algorithm with removing the false matches simultaneously. Experiments show that the algorithm proposed in this paper is effective in the registration of SAR and optical images with large differences.

Paper Details

Date Published: 10 October 2014
PDF: 8 pages
Proc. SPIE 9244, Image and Signal Processing for Remote Sensing XX, 92441C (10 October 2014); doi: 10.1117/12.2175937
Show Author Affiliations
Chunyu Yue, Beijing Institute of Space Mechanics and Electricity (China)
Wanshou Jiang, Wuhan Univ. (China)


Published in SPIE Proceedings Vol. 9244:
Image and Signal Processing for Remote Sensing XX
Lorenzo Bruzzone, Editor(s)

© SPIE. Terms of Use
Back to Top