When we have all of the above mentioned parameters of both the internal and the external orientations, we can start the main part of the procedure. During this, the algorithm computes the real spatial position of all image pixels. Then the image is resampled, using these positions, into a target coordinate system, which was pre-selected by the user. To accomplish this step, we shall know also the elevation of the image points; that’s why a terrain or elevation model is asked for by the algorithm. The accuracy of the elevations can be lower than it was needed for the control point definition at the estimation of the external orientation elements – while the accuracy of one point there affects the whole image, now it controls only its near vicinity.
The result should be always verified, e.g. by a topographic map (practically the one used for control point definition). The horizontal fit is usually the best near to the corner that is the closest one to the vertical axis from the camera. The fit could be unacceptably poor around the far corner, which is caused by the errors of the external element estimation. We can do a feedback to making a new estimation or just retain the good fitting parts of the resulted image (Fig. 60).