A Scale Invariant Feature Transform based matching approach to Unmanned Aerial Vehicles image geo-reference with large rotation angle

Author

Hu, Qingwu ; Ai, Mingyao

Author_Institution

Sch. of Remote Sensing & Inf. Eng., Wuhan Univ., Wuhan, China

fYear

2011

fDate

June 29 2011-July 1 2011

Firstpage

393

Lastpage

396

Abstract

A SIFT (Scale Invariant Feature Transform) based image feature extraction and key points matching approach is proposed for the triangle adjustment calculation of the UAV (Unmanned Aerial Vehicles) images with large rotation angle. The aerial triangle experiment of 16 strips with 787 UAV images shows the SIFT based UAV image matching approach can obtain more than 400 stable image matched key points per image so that it can realize robust external orientation parameters with AT(Aerial Triangle) than the traditional AAT(Automatic Aerial Triangle). The GCPs (Ground Control Points) accuracy of AT is less than 0.4m which can meet the requirement of 1:1000 scale map.

Keywords

aerospace computing; feature extraction; geophysical image processing; image matching; remotely operated vehicles; GCP accuracy; SIFT; aerial triangle experiment; ground control points accuracy; image feature extraction; key point matching approach; robust external orientation parameter; rotation angle; scale invariant feature transform; triangle adjustment calculation; unmanned aerial vehicles image matching; Approximation algorithms; Feature extraction; Remote sensing; Robustness; Software; Strips; Unmanned aerial vehicles; External Orientation; Geo-reference; Matching; SIFT; UAV;

fLanguage

English

Publisher

ieee

Conference_Titel

Spatial Data Mining and Geographical Knowledge Services (ICSDM), 2011 IEEE International Conference on

Conference_Location

Fuzhou

Print_ISBN

978-1-4244-8352-5

Type

conf

DOI

10.1109/ICSDM.2011.5969072

Filename

5969072