A COARSE-TO-FINE CORRELATION ALGORITHM CONSIDERING OCCLUSIONS 
Symposium of Commission III 
Rovaniemi, Finland 
August 19-22, 1986 
Susumu Hattori 
Institute of Industrial Science, Univ. of Tokyo, Japan 
Chuji Mori 
Dep. of Civil Engineering, School of Engineering, 
Okayama University, Japan 
Osamu Uchida 
Asia Air Survey Co. Ltd., Japan 
Abstract: This paper covers a stereo matching algorithm suitable to 
small or middle scale aerial images. Conventional matching algorithm 
based on simple area correlation are often confronted with the 
difficulties: 1) correlation deterioration due to terrain relief 2) 
matching wanderings due to poor textures and 3) matching wanderings in 
occluding areas. The authors propose that for resolving these 
difficulties the so-called coarse-to-fine correlation method should be 
employed. A sophisticated algorithm for stable and precise matching is 
proposed based on coarse-to-fine correlation in the paper. It is featured 
by 1) median-filtering of x-parallaxes to find occlusions and to take off 
wanderings, and 2) narrow-band-pass-filtering of images to get high 
matching precision through coarse-to-fine correlation. 
1. Introduction 
Area correlation has been widely investigated as a practical tool for 
stereo matching of aerial images. But conventional techniques based on 
simple correlation often fail to produce sufficient matching precision 
and stability. The major reasons for it are as follows: 
1) If correlation windows are large compared with spatial frequencies of 
the terrain relief, correlation is suffered from perspective distortions 
and true peaks are often hidden. 
2) If correlation windows are so small as not to contain sufficient 
textures, matchings tend to wander. 
3) If occlusions are contained in images, matchings tend to wander. 
Occlusions means areas that are revealed in one image but not revealed in 
the other image because views are obstructed by some objects. 
As to the difficulties 1) and 2), some authors have already tried to 
solve. Panton et al./6/ suggested a method of adaptive windows: i.e. 
search windows are shaped to be adaptive to corresponding correlation 
windows according to terrain slopes that are predicted from previously 
matched points. Furthermore window sizes are varied according to the 
amounts of textures around the points to be matched. Pertle/8/ 
exploited a matching method of expressing the perspective distortions 
and densitometric distortions in the windows in a linear form, 
coefficients of which are estimated using the iterative least squares 
method to decide conjugate points. Their methods, though very 
attractive, seem to be still insufficient in matching stability. 
On the other hand the difficulty 3) is inherent in area correlation. 
Since area correlation is a method of comparing likelihood between two 
finite areas, it is substantially hard to find occluding areas 
(especially their boundaries) with high precision. Probably on this 
account few investigations have been tried up to now to solve the 
occlusion problem in the photogrammetric field. The authors/1,2,5/ 
asserts that for solving these difficulties so-called coarse-to-fine 
correlation is very useful.  Coarse-to-fine correlation is a multi-step 
procedure from coarse matching in a low frequency domain to fine matching 
in a high frequency domain. In this paper a sophisticated matching 
algorithm for stereo aerial images is discussed with a particular stress 
on how to find occlusions. Briefly to say, occluding areas and poor- 
textured areas can be found step-by-step in the course of a multi-step 
- 317 -