Self-adaptive optical image registration based on optimized analysis of feature points
Image registration is an important preprocessing step for image processing such as change detection,image mosaicking in remote sensing,however a crucial problem involved feature-based image registration is how to reliably establish correspondent features between sensed image and reference image.This paper presents an automatic self-adaptive image registration method based on analytic energy of control points to improve the traditional algorithm.Firstly,an multi-scale segment method based on digital curvelet transform is used to evaluate the quality difference of image pairs,and then self-adaptive parameters of SIFT feature-matching algorithm based on multi-scale grey relation of image quality is proposed to increase the feature points and correspondences; At last,to make sure the accuracy of geometrical transform parameters,a method of correspondences selection based on the distribution and matching energy of control points is developed.Experimental results demonstrate that the proposed method works well in increasing control points and the correspondences of low quality remote sensing images.
Image Registration Scale Invariant Feature Transform (SIFT) Self-adaptive keypoint refinement
Shi Yue Zhang Daobing
Institute of Electronic,Chinese Academy of Sciences,Beijing 100190,China Key Laboratory of Spatial Information Processing and Application System Technology,Chinese Academy o
国内会议
北京
英文
1-7
2013-12-01（万方平台首次上网日期，不代表论文的发表时间）