In: Paparoditis N., Pierrot-Deseilligny M.. Mallet C., Tournaire O. (Eds). IAPRS. Vol. XXXVIII. Part 3A - Saint-Mandé, France. September 1-3. 2010 
ROBUST MATCHING OF AERIAL IMAGES WITH LOW OVERLAP 
M. Mizotin a , G. Krivovyaz a , A. Velizhev a , A. Chemyavskiy b , A. Sechin c 
a Moscow State University, Dept, of Computational Mathematics and Cybernetics, Russia - {mmizotin, gkrivovyaz, 
avelizhev} @graphics.cs.msu.ru 
b State Research Institute of Aviation Systems (FGUP GosNIIAS), Moscow, Russia - achem@gosniias.ru 
c Racurs Co., Moscow, Russia - sechin@racurs.ru 
Commission III, Working Group III/l 
KEY WORDS: Image Matching, Image Registration, Aerial Triangulation, Low Overlap 
ABSTRACT: 
This paper addresses the problem of aerial image matching. We analyze existing approaches to this problem and show that, though 
the modem algorithms cope with the task quite well, their results are deteriorated in case of low overlap and significant rotation 
angle between the images. A two-stage feature-based image matching scheme is presented. It is shown that preliminary stage of 
simplified (shift-rotation) model estimation is crucial in case of low overlap and influences significantly the whole matching scheme. 
We introduce a novel method of shift-rotation model estimation, based on the voting procedure in parameter space, which allows 
finding the correct model in case of extremely difficult input data (overlap area is less than 10%) without using any additional 
information. Finally, the experimental results of our method on both synthetic and real data are presented. We compare our results 
with one of the state of the art SAC-based model estimators and show that our algorithm outperforms existing methods in case of 
very small overlap. 
1. INTRODUCTION 
Automatic aerial image matching, or aerial triangulation, is the 
field of active research at the moment. Matching is necessary 
for further creation of orthophotomaps and 3D modelling, both 
finding an application in such areas as geodesy, cartography, 
Earth monitoring and others. With the rapid development of 
geoinformation systems and the growth of input data amount, a 
fully automated technology of aerial image processing is 
becoming the main goal in this area. 
A lot of different techniques have been introduced recently and 
commercial software is already available on the market. But the 
existing state of the art algorithms still are not able to ensure the 
stable work of automated systems. Because of the complexity of 
aerial images obtaining process, some difficulties inevitably 
appear in the input data. Among them are the cases of very 
small overlap area and significant rotation angle that usually 
occur when matching a whole block of images divided into 
sequences. The aim of our work was to develop a technique that 
outperforms existing matching methods in these cases. Note that 
image scale is assumed to be constant as it is a typical situation 
for aerial images. See Figure 1 for an example of input data. 
The structure of the paper is the following. In Section 2 we 
discuss existing approaches to aerial images matching. The two- 
stage feature-based matching scheme is given in Section 3 and 
the novel voting-based method of shift-rotation model 
estimation is introduced in Section 4. We present our 
experimental results in Section 5. Section 6 concludes the 
paper. 
2. RELATED WORK 
Aerial triangulation operates with hundreds or even thousands 
of images but actually this complex procedure is based on 
image pair matching. Aerial images are usually very large 
(hundreds of mega pixels) making it necessary to use 
hierarchical scale pyramid. 
Figure 1. An example of input aerial images. The overlap area 
(5.7%) detected by the proposed method is outlined