Multi-source Remote Sensing Image Registration Based on Contourlet Transform and Multiple Feature Fusion

被引:19
|
作者
Liu, Huan [1 ,2 ]
Xiao, Gen-Fu [3 ]
Tan, Yun-Lan [1 ,2 ]
Ouyang, Chun-Juan [1 ,2 ]
机构
[1] Jinggangshan Univ, Coll Elect & Informat Engn, Jian 343009, Jiangxi, Peoples R China
[2] Natl Adm Surveying Mapping & Geoinformat NASG, Key Lab Watershed Ecol & Geog Environm Monitoring, Jian 343009, Jiangxi, Peoples R China
[3] Jinggangshan Univ, Coll Mech & Elect, Jian 343009, Jiangxi, Peoples R China
关键词
Feature fusion; multi-scale circle Gaussian combined invariant moment; multi-direction gray level co-occurrence matrix; multi-source remote sensing image registration; contourlet transform; POINT-MATCHING ALGORITHM; SAMPLE CONSENSUS; ROBUST; REPRESENTATION; RECOGNITION;
D O I
10.1007/s11633-018-1163-6
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Image registration is an indispensable component in multi-source remote sensing image processing. In this paper, we put forward a remote sensing image registration method by including an improved multi-scale and multi-direction Harris algorithm and a novel compound feature. Multi-scale circle Gaussian combined invariant moments and multi-direction gray level co-occurrence matrix are extracted as features for image matching. The proposed algorithm is evaluated on numerous multi-source remote sensor images with noise and illumination changes. Extensive experimental studies prove that our proposed method is capable of receiving stable and even distribution of key points as well as obtaining robust and accurate correspondence matches. It is a promising scheme in multi-source remote sensing image registration.
引用
收藏
页码:575 / 588
页数:14
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