Full text: Close-range imaging, long-range vision

A NEW “DIGITAL FILTER” FOR EXTRACTING CONJUGATE POINTS 
ON EPIPOLAR STEREO IMAGES 
P. Patias, V. Tsioukas, L. Sechidis 
The Aristotle University of Thessaloniki, Greece, Dept. of Cadastre, Photogrammetry and Cartography, 
Email : patias@topo.auth.gr 
Commission V, WG V/1 
KEY WORDS: Conjugate points, epipolar images, correlation, image matching, interlaced images 
ABSTRACT: 
The user of a Digital Photogrammetric Station (DPS) usually extracts manually the conjugate points during the restitution procedure 
using epipolar stereo-images. Although the manual procedure is the most secure way for this kind of job it is the most boring and 
tiresome part of a photogrammetric project. One of the advantages of the digital era of Photogrammetry is the automation of the most 
of such tasks. For example, many Digital Photogrammetric Stations have the ability of acquiring automatically conjugate points, 
during the procedure of relative orientation of stereo pair images. The same algorithm can be applied during the restitution procedure 
when epipolar stereo-images are used. The main algorithm that is used for this kind of job is the correlation between the patches of 
the master (e.g. left) and the slave (e.g. right) images of the stereo pair. Additionally the least square image-matching algorithm can 
be applied to enhance the results of the matched points and provide sub-pixel accuracy. 
This method provides the best results under certain circumstances. The correlation procedure should provide a solution very close to 
the correct one. Only under this condition, it is possible for the following image matching technique to provide the sub-pixel 
accuracy of the matching points. When the correlation technique does not provide a good approximate solution (i.e. less than 2-3 
pixel away from the correct conjugate point) it is unavoidable that the least square image technique will fail. 
The proposed technique tries to fill the algorithmic gap between the correlation and the least squares image-matching technique in 
the above-mentioned procedure. Actually it concerns a method that generally speaking resembles a digital filter. Two very important 
advantages of the proposed method are speed and efficiency. It is much faster than the typical correlation and least square image 
matching technique and can be applied directly to the interlaced stereo-image. By using the simple zooming technique on the 
interlaced stereo-image it can provide sub-pixel accuracy of the conjugate point location. Furthermore, it can be used in automatic 
restitution, by estimating the position of the conjugate points in real-time. 
1. INTRODUCTION - PROBLEM STATEMENT provides accuracies of 0.1 pixels, but may also lead to errors in 
the presence of high noise or when the correlation process does 
The restitution process is considered to be the last part of a not provide a good initial solution. 
digital photogrammetic project. It is certainly the most boring 
and tiresome process and it contains the smallest amount of 
automation in a DPS. Although, the conjugate point collection 2. IMAGE FOCUS-DEFOCUS - MATCHING 
has been used for several process in a photogrammetric project 
(image point matching is used during the relative orientation Something that has never been used before from the 
and in the automatic procedure of DTM generation) it has not photogrammetrists in the past is the processing of the interlaced 
been applied for automated restitution. image that supplies to the user the 3D view of the imaged 
objects from their epipolar images, as one single image that is 
  
  
  
This is due to several reasons and the most important is the 
inability to determine accurately (less than one pixel) the 
conjugate points on the images of a stereo-pair. On the 
contrary, the manual collection of stereo-restitution is able to 
do so. After all, manual editing of the automatic restituted 
object should follow and since the editing procedure is much 
more difficult than the original manual restitution the 
automation is avoided. 
Another problem that also appears is the great amount of time 
that is demanded for this kind of job. In most cases the 
combination of cross correlation and least squares matching is 
applied. The first part of the automatic process (correlation) 
supplies accuracies to the order of one pixel, while the second 
process is a very time consuming algorithm, which optimally 
characterized by some very specific features. This image can be 
processed as any other image; digital filters may be applied on 
it and image statistics may be used to provide useful 
information. This image is actually two images in a composite 
one, since its odd rows come from the left epipolar image and 
the even from the right one. Its main feature is the extremely 
high gradient along the y-axis that may appear when the image 
does not provide a correct stereo viewing of the imaged object. 
In the case when the roaming of the epipolar images brings into 
coincidence the points of the epipolar images, providing a 
correct stereo viewing, the gradient of the images even along 
the y-axis is low. Concluding we may say that the high textured 
images that are provided from the stereo viewing system are 
not correct while low textured images are correctly matched. 
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