Two-dimensional signal and image processing
Two-dimensional signal and image processing
Markov random field modeling in computer vision
Markov random field modeling in computer vision
Primal-dual interior-point methods
Primal-dual interior-point methods
Interior point algorithms: theory and analysis
Interior point algorithms: theory and analysis
An efficient algorithm for image segmentation, Markov random fields and related problems
Journal of the ACM (JACM)
Iterative Methods for Sparse Linear Systems
Iterative Methods for Sparse Linear Systems
Convex Optimization
Second-order Cone Programming Methods for Total Variation-Based Image Restoration
SIAM Journal on Scientific Computing
Efficient Minimization Methods of Mixed l2-l1 and l1-l1 Norms for Image Restoration
SIAM Journal on Scientific Computing
Iterative Total Variation Regularization with Non-Quadratic Fidelity
Journal of Mathematical Imaging and Vision
An Interior-Point Method for Large-Scale l1-Regularized Logistic Regression
The Journal of Machine Learning Research
Nonlinear Optimization
Mathematical programming algorithms for regression-based nonlinearfiltering in RN
IEEE Transactions on Signal Processing
Iterative image restoration using approximate inverse preconditioning
IEEE Transactions on Image Processing
Fast, robust total variation-based reconstruction of noisy, blurred images
IEEE Transactions on Image Processing
Blind Deconvolution Using a Variational Approach to Parameter, Image, and Blur Estimation
IEEE Transactions on Image Processing
| Hi-index | 35.68 |
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.