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

Donald Dean Duncan; Sean J. Kirkpatrick

doi:10.1117/12.477914

27 August 2003 Maximum-likelihood estimators for one- and two-dimensional speckle motion

Proceedings Volume 4961, Laser-Tissue Interaction XIV; (2003) https://doi.org/10.1117/12.477914
Event: Biomedical Optics, 2003, San Jose, CA, United States

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.

Citation Download Citation

Donald Dean Duncan and Sean J. Kirkpatrick "Maximum-likelihood estimators for one- and two-dimensional speckle motion", Proc. SPIE 4961, Laser-Tissue Interaction XIV, (27 August 2003); https://doi.org/10.1117/12.477914

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available