Remote Sensing Image Registration Based on Multifeature and Region Division

被引：18
作者：
Ma, Wenping [1 ]
Wu, Yue [2 ]
Zheng, Yafei [1 ]
Wen, Zelian [1 ]
Liu, Liang [1 ]
机构：
[1] Xidian Univ, Key Lab Intelligent Percept & Image Understanding, Minist Educ, Int Res Ctr Intelligent Percept & Computat, Xian 710071, Shaanxi, Peoples R China
[2] Xidian Univ, Sch Comp Sci & Technol, Xian 710071, Shaanxi, Peoples R China
来源：
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS | 2017年 / 14卷 / 10期
基金：
中国国家自然科学基金;
关键词：
Harris feature; image registration; region division; scale-invariant feature transform (SIFT); SAMPLE CONSENSUS; ALGORITHM; SIFT;
D O I：
10.1109/LGRS.2017.2728604
中图分类号：
P3 [地球物理学]; P59 [地球化学];
学科分类号：
0708 ; 070902 ;
摘要：
Although many feature-based registration methods have been proposed, automatic image registration is still a challenging task due to the influence of various conditions and uncertain difficulties for remote sensing images. In this letter, a novel image registration method, including two types of feature detectors and a region boundary constraint strategy for matching, is proposed. Two types of features detected by scale-invariant feature transform and Harrisv operators have advantages of keeping different structural information in the image and increasing the number of keypoints for later matching. Afterward, a region boundary constraint strategy based on the image sketch map is utilized in matching step. This strategy restricts the detected two types of features in their respective structural region and nonstructural region to reduce the incorrect correspondences. Experimental results demonstrate the superiority of our proposed registration algorithm compared with other research works in terms of correct matching number and aligning accuracy.
引用
收藏
页码：1680 / 1684
页数：5
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