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Proceedings Paper

Maximum-likelihood estimators for one- and two-dimensional speckle motion
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Paper Abstract

Presented herein is a maximum likelihood (ML) estimator for assessing small motions in speckle patterns. Estimators of this kind are important in a variety of speckle techniques used in non-destructive evaluation. These speckle patterns can be two-dimensional (one spatial dimension and one temporal dimension) as obtained in objective speckle techniques or three-dimensional (two spatial dimensions and one temporal dimension) as seen in subjective (imaged) speckle methods. The specific estimator discussed herein is appropriate for assessing strain in two dimensional subjective patterns. We demonstrate good performance of this estimator for speckle motions of a small portion of a pixel. Beyond this point, more conventional approaches (e.g., correlation) have been shown to perform well. This maximum likelihood estimator can be implemented easily with simple linear image processing filtering techniques.

Paper Details

Date Published: 27 August 2003
PDF: 7 pages
Proc. SPIE 4961, Laser-Tissue Interaction XIV, (27 August 2003); doi: 10.1117/12.477914
Show Author Affiliations
Donald Dean Duncan, Johns Hopkins Univ. (United States)
Sean J. Kirkpatrick, Providence St. Vincent Medical Ctr. (United States)

Published in SPIE Proceedings Vol. 4961:
Laser-Tissue Interaction XIV
Donald Dean Duncan; Sean J. Kirkpatrick; Andres Kriete; Steven L. Jacques, Editor(s)

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