HIGH PRECISION DEM GENERATION FROM SPOT STEREO IMAGERY BY 
OBJECT SPACE LEAST SQUARES MATCHING 
K. C. LO , N. J. MULDER 
I.T.C. 
P.O.Box 6, 7500 AA Enschede 
The Netherlands 
(ISPRS Commission III) 
Abstract: 
For automatic DEM generation from multiple view SPOT imagery with high precision, an approach 
of "Refinement from Coarse" is proposed. In the coarse DEM generation stage, in contrast with 
the traditional methods which match at intensity level in image space with the signal 
processing technique, the concept of Knowledge Engineering is used to perform high level 
Feature Matching by Property List and String Matching for Correspondence analysis with high 
reliability. In the refinement stage, the Object Space Least Squares Matching method, which 
is the most rigorous method from a theoretical viewpoint, is proposed for coarse DEM 
refinement. This method is different from the traditional two-step approach which matches the 
corresponding point in image space first, and then determines the DEM by Space Intersection; 
this method is improved by back mapping the image data into object space to get object 
reflectance D(x,y) with referring the object surface Z(x,y), and perform matching in object 
space. It is simultaneously to determine two functions in the object space: the terrain relief 
Z(x,y) and the terrain reflectance D(x,y) in one solution with least squares adjustment 
iteratively. The disadvantages of matching in image space which the multi view image of the 
same object has different geometric or reflectance distortion can be avoided. It's flexibility 
allows the user to handle more than two SPOT multi-view images in one solution, which increases 
accuracy and reliability as well. It is good for SPOT images which offer the resolution with 
10 meters groundel size only. 
Key Words: DEM, Correspondence Analysis, Property List, String Matching, 
Object Space Least Squares Matching. 
I. INTRODUCTION automatic generation of coarse DEM data by Linear 
Feature Matching. In order to plan and execute 
The generation of a GIS for a 3-D object oriented complicated sequence of operations and functions, 
data base is required urgently in many countries. we believe the methods of Knowledge Engineering 
The automatic extraction of 2.5-D information from should be used, and Correspondence Analysis will 
SPOT stereo images is, potentially, an efficient be based on object detection with geometric defi- 
and economic way. Some on-line (real time) com- nition and object description by means of Property 
mercial systems have appeared in prototype, but Lists [Mulder et al.,1988]. The selection / repre- 
the methods of the off-line system for recons- sentation and use of proper knowledge is a central 
tructing the earth surface with high quality and problem in research. A range of different knowl- 
acceptable economy must be researched and further edge representation techniques must be developed, 
developed still; We want to establish a system for along with a number of approaches to applying 
generating DEM with high accuracy / high quality knowledge, which are concerned in the field of 
/ high reliability with the support of the method Meta-Level Knowledge. 
of Object Space Least Squares Matching. It will 
then offer good fundamental 2.5-D information to 2.3 Object Space Minimum Cost Matching 
GIS for multi-purpose applications. 
Traditional matching in Image Space has the short- 
  
  
2. BACKGROUND PROBLEMS coming that the same object in multi-view images 
appears with different geometric distortions and 
2.1 SPOT Satellite Imagery radiometry. The geometric distortions are caused 
; by the central perspective which produces relief 
Since the SPOT imagery is acquired by push-broom displacement in the image; the tilt of the sensor 
scanners, the imaging geometry is different from (SPOT has off nadir angle from O to 27 degrees) 
the conventional central perspective photographs causes tilt displacement in the image. As the 
with frame camera, and the orbit parameters multi-view SPOT images are taken at different 
require simulate dynamic modelling. For solving positions, at different times or under different 
the inverse camera model problems, the point in illumination conditions, this produces different 
issue is how to determine the orientation parame- radiometry for the same object in different 
ters of each scan line with sufficient accuracy images. These geometric and radiometric differ- 
(e.g. improving the accuracy of Tie Point measure- ences produce matching failures or reduce the 
ment/transfer and best pattern of Ground Control accuracy. Therefore, motivation for improved 
Point distribution) and at lowest cost (e.g. developments should come from the realization that 
minimum number of Ground Control Points). On the all information in images is inherent in the 
other hand, the CCT of SPOT not only presents object space, and the transformation of the 
imagery data, but also offers special on board matching problem from Image Space to Object Space 
auxiliary data, such as information about posi- leads to a unified and precise approach where 
tion, attitude, look direction, radiometric all available knowledge is referenced to the 
calibration of scene/sensor [SPOT User's Handbook, same basis. Research has to be carried out into 
1988]; how to fully use this information for ways of how to model the surface of the terrain 
obtaining benefits in Aerial Triangulation ( A.T.) and its reflection which is suitable for matching 
and DEM generation stage must be considered in properly and efficiently. 
every phase of image data processing. On the other hand, high accuracy can be obtained 
by using Minimum Cost Matching; e.g. the Minimum 
2.2 Knowledge Engineering Euclidean Distance can be selected as the "Cost" 
in Euclidean space for similarity assessment. 
The existing methods of signal correlation and Because, in case the distance is small, the dis- 
feature matching are limited for handling some tance behaves as SIN function of the angle which 
special correspondence analysis problems, such as is between the Feature Vectors for matching, it 
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