Parametric Image Alignment Using Enhanced Correlation Coefficient Maximization

In this work we propose the use of a modified version of the correlation coefficient as a performance criterion for the image alignment problem. The proposed modification has the desirable characteristic of being invariant with respect to photometric distortions. Since the resulting similarity measu...

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Veröffentlicht in:	IEEE transactions on pattern analysis and machine intelligence Jg. 30; H. 10; S. 1858 - 1865
Hauptverfasser:	Evangelidis, G.D., Psarakis, E.Z.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Los Alamitos, CA IEEE 01.10.2008 IEEE Computer Society The Institute of Electrical and Electronics Engineers, Inc. (IEEE) Institute of Electrical and Electronics Engineers
Schlagworte:	Additives Algorithms Alignment Applied sciences Artificial Intelligence Closed-form solution Computational complexity Computational modeling Computer Science Computer science; control theory; systems Computer Simulation Computer Vision and Pattern Recognition Distortion measurement Exact sciences and technology Gradient methods Image Enhancement - methods Image Interpretation, Computer-Assisted - methods Image Processing and Computer Vision Inverse Iterative methods Mathematical analysis Mathematical models Maximization Models, Statistical Motion Nonlinear distortion Pattern Recognition, Automated - methods Pattern recognition. Digital image processing. Computational geometry Photometry Predistortion Registration Studies Subtraction Technique Testing Motion Gradient methods Registration Image Processing and Computer Vision Correlation coefficient Invariant Image registration Correlation Motion estimation Similarity Image processing Iterative method parametric motion Computational complexity Modeling Optimization Inverse problem Exact solution Alignment Metric Objective function Pattern analysis Artificial intelligence Gradient method gradient methods Photometry
ISSN:	0162-8828, 1939-3539
Online-Zugang:	Volltext
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Zusammenfassung:	In this work we propose the use of a modified version of the correlation coefficient as a performance criterion for the image alignment problem. The proposed modification has the desirable characteristic of being invariant with respect to photometric distortions. Since the resulting similarity measure is a nonlinear function of the warp parameters, we develop two iterative schemes for its maximization, one based on the forward additive approach and the second on the inverse compositional method. As it is customary in iterative optimization, in each iteration the nonlinear objective function is approximated by an alternative expression for which the corresponding optimization is simple. In our case we propose an efficient approximation that leads to a closed form solution (per iteration) which is of low computational complexity, the latter property being particularly strong in our inverse version. The proposed schemes are tested against the forward additive Lucas-Kanade and the simultaneous inverse compositional algorithm through simulations. Under noisy conditions and photometric distortions our forward version achieves more accurate alignments and exhibits faster convergence whereas our inverse version has similar performance as the simultaneous inverse compositional algorithm but at a lower computational complexity.
Bibliographie:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 ObjectType-Article-2 ObjectType-Feature-1 content type line 23
ISSN:	0162-8828 1939-3539
DOI:	10.1109/TPAMI.2008.113