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Performance Evaluations of Correlations of Digital Images Using Different Separability Measures

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1 Author(s)
Sadjadi, F.A. ; Department of Electrical Engineering, University of Tennessee, Knoxville, TN 37916.

A comparison of four separability measures which are useful in the registration of two-dimensional images is presented. Bayes probability of error, Chernoff bound, Bhattacharyya bound, and Fisher's criteria are used in the selection of the appropriate reference images from a set of aerial pictures, each exhibiting a different view of a scene, i.e., down-looking and target-looking. The experiment is repeated for corresponding synthetic images of this scene. Both area and edge correlations are used. A comparison of the measures and the resulting probabilities of error is made. The results show that for real images the target-looking view performs better than the down-looking view for both area and edge correlations. For synthetic images, the down-looking view performs better than the target-looking view for both area and edge correlations. The variation in synthetic images between the target-looking and the down-looking views is larger than in the real images for both area and edge correlations.

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Pattern Analysis and Machine Intelligence, IEEE Transactions on  (Volume:PAMI-4 ,  Issue: 4 )