Abstract
The effect of geometric distortion on the local accuracy of the image registration algorithms using cross correlation is presented. Using a probabilistic model describing images as homogeneous random patterns, expressions for the mean and covariance of the local error vector in terms of image and noise autocorrelation functions, geometric distortion, and reference image area are derived. The geometric distortions considered are those represented by an affine transformation of image coordinates. It is shown that for a fixed geometric distortion there is an image size (integration area) that minimizes the local error. The optimum area decreases with increasing geometric distortion.
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