Cart (Loading....) | Create Account
Close category search window
 

Optimal Estimation of Deterioration From Diagnostic Image Sequence

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

5 Author(s)
Gorinevsky, D. ; Dept. of Electr. Eng., Stanford Univ., Stanford, CA ; Seung-Jean Kim ; Beard, S. ; Boyd, S.
more authors

Estimation of mechanical structure damage can greatly benefit from the knowledge that the damage accumulates irreversibly over time. This paper formulates a problem of estimation of a pixel-wise monotonic increasing (or decreasing) time series of images from noisy blurred image data. Our formulation includes temporal monotonicity constraints and a spatial regularization penalty. We cast the estimation problem as a large-scale quadratic programming (QP) optimization and describe an efficient interior-point method for solving this problem. The method exploits the special structure of the QP and scales well to problems with more than a million of decision variables and constraints. The proposed estimation approach performs well for simulated data. We demonstrate an application of the approach to diagnostic images obtained in structural health monitoring experiments and show that it provides a good estimate of the damage accumulation trend while suppressing spatial and temporal noises.

Published in:

Signal Processing, IEEE Transactions on  (Volume:57 ,  Issue: 3 )

Date of Publication:

March 2009

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.