DocumentCode :
3365304
Title :
Multi-spectral remote sensing image registration via spatial relationship analysis on sift keypoints
Author :
Hasan, Mahmudul ; Jia, Xiuping ; Robles-Kelly, Antonio ; Zhou, Jun ; Pickering, Mark R.
Author_Institution :
Sch. of Eng. & Inf. Technol., Univ. of New South Wales, Canberra, ACT, Australia
fYear :
2010
fDate :
25-30 July 2010
Firstpage :
1011
Lastpage :
1014
Abstract :
Multi-sensor image registration is a challenging task in remote sensing. Considering the fact that multi-sensor devices capture the images at different times, multi-spectral image registration is necessary for data fusion of the images. Several conventional methods for image registration suffer from poor performance due to their sensitivity to scale and intensity variation. The scale invariant feature transform (SIFT) is widely used for image registration and object recognition to address these problems. However, directly applying SIFT to remote sensing image registration often results in a very large number of feature points or keypoints but a small number of matching points with a high false alarm rate. We argue that this is due to the fact that spatial information is not considered during the SIFT-based matching process. This paper proposes a method to improve SIFT-based matching by taking advantage of neighborhood information. The proposed method generates more correct matching points as the relative structure in different remote sensing images are almost static.
Keywords :
image fusion; image registration; object recognition; remote sensing; data fusion; multisensor devices; multisensor image registration; multispectral image registration; multispectral remote sensing image registration; neighborhood information; object recognition; scale invariant feature transform; spatial relationship analysis; Earth; Image registration; Pixel; Registers; Remote sensing; Satellites; Sensors; Image registration; SIFT; local weighted mean;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2010 IEEE International
Conference_Location :
Honolulu, HI
ISSN :
2153-6996
Print_ISBN :
978-1-4244-9565-8
Electronic_ISBN :
2153-6996
Type :
conf
DOI :
10.1109/IGARSS.2010.5653482
Filename :
5653482
Link To Document :
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