SIFT Based Automatic Tie-Point Extraction for Multitemporal SAR Images

Author

Liu, Lining ; Wang, Yunhong ; Wang, Yiding

Author_Institution

Sch. of Comput. Sci. & Eng., Beihang Univ., Beijing

Volume

1

fYear

2008

fDate

21-22 Dec. 2008

Firstpage

499

Lastpage

503

Abstract

Tie-point extraction is the key step of coregistration of multitemporal images. In this paper, Scale invariant feature transformation (SIFT) is applied to extract tie-points from multitemporal SAR images. A histogram-based preprocessing method and the optimization of SIFT parameters are proposed for increasing the number of correct tie-points. We explore the performance of SIFT algorithm on different topographic ENVISAT SAR images. The experimental results show that these methods are robust to speckle noise and can markedly improve the performance of SIFT on SAR images.

Keywords

feature extraction; image registration; optimisation; synthetic aperture radar; automatic tie-point extraction; histogram-based preprocessing method; multitemporal SAR images; multitemporal image coregistration; scale invariant feature transformation; topographic ENVISAT SAR images; Computer science; Computer science education; Data mining; Educational institutions; Educational technology; Feature extraction; Filters; Geoscience and remote sensing; Optimization methods; Remote sensing;

fLanguage

English

Publisher

ieee

Conference_Titel

Education Technology and Training, 2008. and 2008 International Workshop on Geoscience and Remote Sensing. ETT and GRS 2008. International Workshop on

Conference_Location

Shanghai

Print_ISBN

978-0-7695-3563-0

Type

conf

DOI

10.1109/ETTandGRS.2008.38

Filename

5070205