MULTI-CRITERIONS FOR SIMILARITY ASSESSMENT 
IN PHOTOGRAMETRIC IMAGE CORRELATION 
Lin Zongjian 
Wuhan Technical University of Surveying and Mapping 
Wuhan, China 
ABSTRACT 
Several conventional similarity criterions in photogrammetric 
image correlation are analysed by the use of vector algebra. 
Theoretical imperfections of these criterions are discussed. 
As a result, an algorithm with dual or triplex criterions for 
stereo image matching is proposed. It has been verified by 
theory as well as experiments, that the new method can give 
better results than the methods with correlation coefficient 
algorithm or with other single criterion, when both reliabi- 
lity and speed of computation are considered. 
1. INTRODUCTION 
Similarity assessment plays an important part in photogram- 
metric image correlation. Helava(1976), Dowman and Haggag 
(1977) have made many investgations to eveluate the simila- 
rity critérions. The results from their experiments shows 
that every criterion has its advantages and disadvantages 
different from the others. In general, the correlation coef- 
ficient criterion gives best quality and takes longest com- 
putation time. 
In order to make a theoretical elucidation of the relations 
and differences among the criterions and explore better paths 
for similarity assessment, a method using vector algebra for 
analysis of similarity criterions is accepted. 
2. ANALYSIS OF THE CRITERIONS 
In thise paper, the scope of image correlation/ or matching 
is limited in photogrammetric field to seek the parallaxes 
from the digitized stereo images. Several criterions applied 
to conventional correlation algorithms can be briefly de- 
scribed as following. 
(a) Covariance 
0,,2 & (0, — a) (b; — b) — max ( 15 
i=1 
Where a4 and b4 indicate the grey level with pixel number i 
respectively in left image patch and in right image patch of 
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