DocumentCode
3405986
Title
Sign ambiguity resolution for phase demodulation in interferometry with application to prelens tear film analysis
Author
Wu, Dijia ; Boyer, Kim L.
Author_Institution
Rensselaer Polytech. Inst., Troy, NY, USA
fYear
2010
fDate
13-18 June 2010
Firstpage
2807
Lastpage
2814
Abstract
We present a novel method to solve sign ambiguity for phase demodulation from a single interferometric image that possibly contains closed fringes. The problem is formulated in a binary pairwise energy minimization framework based on phase gradient orientation continuity. The objective function is non-submodular and therefore its minimization is an NP-hard problem, for which we devise a multigrid hierarchy of quadratic pseudoboolean optimization problems that can be improved iteratively to approximate the optimal solutions. Compared with traditional path-following phase demodulation methods, the new approach does not require any heuristic scanning strategy, it is not subject to the propagation of error, and the extension to three dimensional fringe patterns is straightforward. A set of experiments with synthetic data and real prelens tear film interferometric images of the human eye demonstrate the effectiveness and robustness of the proposed algorithm in comparison with existing state-of-the-art phase demodulation methods.
Keywords
computational complexity; demodulation; image processing; interferometry; minimisation; NP-hard problem; binary pairwise energy minimization framework; closed fringes; error propagation; heuristic scanning strategy; human eye; interferometry; multigrid hierarchy; path-following phase demodulation methods; phase gradient orientation continuity; prelens tear film analysis; quadratic pseudoboolean optimization problems; sign ambiguity resolution; single interferometric image; tear film interferometric images; three dimensional fringe patterns; Demodulation; Helium; Histograms; Image coding; Image retrieval; Image storage; Interferometry; Large-scale systems; Quantization; Vocabulary;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Vision and Pattern Recognition (CVPR), 2010 IEEE Conference on
Conference_Location
San Francisco, CA
ISSN
1063-6919
Print_ISBN
978-1-4244-6984-0
Type
conf
DOI
10.1109/CVPR.2010.5540011
Filename
5540011
Link To Document