Robust and Precise Registration of Oblique Images Based on Scale-Invariant Feature Transformation Algorithm

Author

Huachao, Yang ; Shubi, Zhang ; Yongbo, Wang

Author_Institution

Inst. of Photogrammetry & Remote Sensing, China Univ. of Min. & Technol., Xuzhou, China

Volume

9

Issue

4

fYear

2012

fDate

7/1/2012 12:00:00 AM

Firstpage

783

Lastpage

787

Abstract

The automatic registration of oblique images taken at different viewpoints remains a challenge until today. Based on scale-invariant feature transformation (SIFT) algorithm, a robust and accurate weighted least square matching (LSM) (SIFT/LSM) method modeled using 2-D projective transformation is proposed for highly accurate registration of oblique images. Normalized cross correlation (NCC) metric modified by an adaptive scale and orientation of SIFT features (SIFT/NCC) is proposed to obtain a good initial estimation for the SIFT/LSM. For practical use, image matching is implemented using a coarse-to-fine multistage strategy by sequentially incorporating the standard SIFT algorithm, SIFT/NCC, and SIFT/LSM. Experiments conducted on oblique images of real-world scenes demonstrate the feasibility of the proposed approach.

Keywords

image matching; image registration; least squares approximations; 2-D projective transformation; automatic registration; coarse-to-fine multistage strategy; image matching; normalized cross correlation metric; oblique image registration; scale-invariant feature transformation algorithm; weighted least square matching method; Accuracy; Equations; Estimation; Mathematical model; Robustness; Vectors; Affine invariant; image registration; least square matching (LSM); oblique images; scale-invariant feature transformation (SIFT);

fLanguage

English

Journal_Title

Geoscience and Remote Sensing Letters, IEEE

Publisher

ieee

ISSN

1545-598X

Type

jour

DOI

10.1109/LGRS.2011.2181485

Filename

6151023