INTEGRATION OF DIGITAL IMAGE MATCHING AND MULTI IMAGE SHAPE FROM SHADING 
C. Heipke 
Chair for Photogrammetry and Remote Sensing 
Technical University Munich 
Arcisstr. 21, D-8000 Munich 2, Germany 
Tel: +49-89-2105 2671; Fax: +49-89-280 95 73; Telex: 522854 tumue d 
E-mail: heipke@photo.verm.tu-muenchen.de 
Commission III 
ABSTRACT: 
Classical shape from shading (SFS) is based on the 
analysis of the intensity values of a single digital image in 
order to derive three dimensional information of the 
depicted scene. It involves the orthographic projection 
for the transformation from object to image space and 
has been successfully applied to weakly textured images. 
In general the illumination conditions must be known, 
Lambertian reflection and constant albedo must be as- 
sumed for the object surface, and only surface slopes can 
be determined. Digital image matching for photogram- 
metric processing on the other hand needs at least two 
images of the same scene taken from different view 
points and the images must be well textured. Therefore, 
the two methods are complementary to each other, and 
a combined model should yield better results than any 
of the two separate ones. 
In this paper a new global approach is presented inte- 
grating digital image matching and multi image SFS in 
object space. In aleast squares adjustment the unknowns 
(geometric and radiometric parameters of the object 
surface) are estimated from the pixel intensity values and 
control information. The perspective projection is used 
for the transformation from object to image space. 
The approach is investigated using synthetic images. The 
main results of this study are the following: 
- Heights of a digital terrain model (DTM) or a digital 
surface model (DSM) instead of surface slopes can 
be calculated directly using multi image SFS alone 
or the combined approach (in this paper the term 
"DTM" denotes a classical DTM as well as a DSM). 
- There is no need for conjugate points in the multi 
image SFS approach. This is especially important, 
832 
since in weakly textured images the correspondence 
problem is extremely hard to solve due to the lack of 
large image intensity gradients. 
- If variable albedo is present in parts of the object 
surface only the combined approach yields correct 
results. Multi image SFS and digital image matching 
alone fail in this case. 
Key Words: digital photogrammetry, shape from sha- 
ding, image matching, image analysis, DTM/DSM, theo- 
ry 
1. INTRODUCTION 
One of the main difficulties of digital photogrammetry 
presents the automatic measurement of image coordina- 
tes of conjugate points for the computation of object 
space coordinates. This problem is referred to as "digital 
image matching". It has been a focus of research for 
nearly thirty years. Early work goes back to Sharp et al. 
/1965/. During the years many algorithms have been 
suggested for this task. The state-of-the-art of digital 
image matching is the use of a global, multi image, object 
based approach incorporating a hierarchical procedure 
to provide initial values for the unknown parameters. 
While feature based matching is faster and seems to be 
more robust, least squares matching has been found to 
be more accurate. However, it can be observed, that all 
algorithms, regardless of their origin in detail, heavily 
rely on the presence of image texture. In the absence of 
sufficient image intensity gradients, every matching al- 
gorithm will fail to produce correct results. 
The rarity of high resolution stereoscopic images of 
planetary surfaces as well as research in computer vision 
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