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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Bibliographic Details
Published in:IEEE transactions on pattern analysis and machine intelligence Vol. 30; no. 10; pp. 1858 - 1865
Main Authors: Evangelidis, G.D., Psarakis, E.Z.
Format: Journal Article
Language:English
Published: 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
Subjects:
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 Access:Get full text
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Description
Summary: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.
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ISSN:0162-8828
1939-3539
DOI:10.1109/TPAMI.2008.113