Unwrapping Hartmann-Shack Images of Off-Axis Aberration using Artificial Centroid Injection Method

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dc.contributor.author Yuwono, M
dc.contributor.editor Ding, Y
dc.date.accessioned 2012-10-12T03:36:31Z
dc.date.issued 2011-01
dc.identifier.citation 2011 4th International Conference on Biomedical Engineering and Informatics (BMEI), 2011, pp. 560 - 564
dc.identifier.isbn 978-1-4244-9351-7
dc.identifier.other E1 en_US
dc.identifier.uri http://hdl.handle.net/10453/19271
dc.description.abstract As the degree of aberration and noise increases, particularly for off-axis aberration, wavefronts of Hartmann-Shack images become so distorted that special care needs to be considered in order to successfully and gracefully unwrap the images. This paper proposes an alternative algorithmic approach called the artificial centroid injection method. Initial centroid extraction is done using Laplacian of Gaussian (LoG) and dynamic thresholding. Outlier centroids are filtered using ensemble of weak classifiers boosted with Adaboost algorithm. Observing the nature of the vertical and horizontal centroid sequences using Kalman Filter, multiple General Regression Neural Networks (GRNN) are then trained to approximate centroid sequences. Artificial centroids are generated by taking the intersection points of approximated vertical and horizontal GRNN sequences that occurs inside an elliptical Region of Interest optimized with Regrouping Particle Swarm (RegPSO). These artificial centroids are injected to the intial centroid vector to predictively recover missing and previously unrecognized spots. Wavefront algorithm is then applied to correspond detected centroids to their appropriate lenslet centers. This algorithm has successfully unwrapped 29 different off-axis aberration HS images, -50° Temporal plane to +50° Nasal plane up to zero pixel prediction error, with no false correlations in any of the tested images.
dc.format Scott McWhirter
dc.publisher IEEE
dc.relation.isbasedon 10.1109/BMEI.2011.6098352
dc.title Unwrapping Hartmann-Shack Images of Off-Axis Aberration using Artificial Centroid Injection Method
dc.type Conference Proceeding
dc.parent 2011 4th International Conference on Biomedical Engineering and Informatics (BMEI)
dc.journal.number en_US
dc.publocation Piscataway, USA en_US
dc.publocation Piscataway, USA
dc.publocation Piscataway, USA
dc.publocation Piscataway, USA
dc.publocation Piscataway, USA
dc.publocation Piscataway, USA
dc.identifier.startpage 560 en_US
dc.identifier.endpage 564 en_US
dc.cauo.name FEIT.Faculty of Engineering & Information Technology en_US
dc.conference Verified OK en_US
dc.conference International Conference on Biomedical Engineering and Informatics (BMEI)
dc.conference International Conference on Biomedical Engineering and Informatics (BMEI)
dc.conference International Conference on Biomedical Engineering and Informatics (BMEI)
dc.conference International Conference on Biomedical Engineering and Informatics (BMEI)
dc.conference International Conference on Biomedical Engineering and Informatics (BMEI)
dc.for 0903 Biomedical Engineering
dc.personcode 112628
dc.percentage 100 en_US
dc.classification.name Biomedical Engineering en_US
dc.classification.type FOR-08 en_US
dc.edition en_US
dc.custom International Conference on Biomedical Engineering and Informatics (BMEI) en_US
dc.date.activity 20111015 en_US
dc.date.activity 2011-10-15
dc.date.activity 2011-10-15
dc.date.activity 2011-10-15
dc.date.activity 2011-10-15
dc.date.activity 2011-10-15
dc.location.activity Shanghai, China en_US
dc.location.activity Shanghai, China
dc.location.activity Shanghai, China
dc.location.activity Shanghai, China
dc.location.activity Shanghai, China
dc.location.activity Shanghai, China
dc.description.keywords Adaboost algorithm , GRNN , Hartmann-Shack image unwrapping , Kalman filter , Laplacian of Gaussian thresholding , RegPSO , artificial centroid injection method , centroid sequences , dynamic thresholding , multiple general regression neural networks , noise , off-axis aberration , regrouping particle swarm optimisation , wavefront algorithm en_US
dc.description.keywords Adaboost algorithm , GRNN , Hartmann-Shack image unwrapping , Kalman filter , Laplacian of Gaussian thresholding , RegPSO , artificial centroid injection method , centroid sequences , dynamic thresholding , multiple general regression neural networks , noise , off-axis aberration , regrouping particle swarm optimisation , wavefront algorithm
dc.description.keywords Adaboost algorithm , GRNN , Hartmann-Shack image unwrapping , Kalman filter , Laplacian of Gaussian thresholding , RegPSO , artificial centroid injection method , centroid sequences , dynamic thresholding , multiple general regression neural networks , noise , off-axis aberration , regrouping particle swarm optimisation , wavefront algorithm
dc.description.keywords Adaboost algorithm , GRNN , Hartmann-Shack image unwrapping , Kalman filter , Laplacian of Gaussian thresholding , RegPSO , artificial centroid injection method , centroid sequences , dynamic thresholding , multiple general regression neural networks , noise , off-axis aberration , regrouping particle swarm optimisation , wavefront algorithm
dc.description.keywords Adaboost algorithm , GRNN , Hartmann-Shack image unwrapping , Kalman filter , Laplacian of Gaussian thresholding , RegPSO , artificial centroid injection method , centroid sequences , dynamic thresholding , multiple general regression neural networks , noise , off-axis aberration , regrouping particle swarm optimisation , wavefront algorithm
dc.description.keywords Adaboost algorithm , GRNN , Hartmann-Shack image unwrapping , Kalman filter , Laplacian of Gaussian thresholding , RegPSO , artificial centroid injection method , centroid sequences , dynamic thresholding , multiple general regression neural networks , noise , off-axis aberration , regrouping particle swarm optimisation , wavefront algorithm
pubs.embargo.period Not known
pubs.organisational-group /University of Technology Sydney
pubs.organisational-group /University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group /University of Technology Sydney/Students


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