19 citations · 66 across the 12 of their papers we have counts for
13 papers
Unbiased Bregman-Risk Estimators: Application to Regularization Parameter Selection in Tomographic Image Reconstruction
Elias S. Helou, Sandra A. Santos, Lucas E. A. Simões
Unbiased estimators are introduced for averaged Bregman divergences which generalize Stein's Unbiased (Predictive) Risk Estimator, and the minimization of these estimators is propo…
A Markovian Incremental Stochastic Subgradient Algorithm
Rafael Massambone, Eduardo F. Costa, Elias S. Helou
A stochastic incremental subgradient algorithm for the minimization of a sum of convex functions is introduced. The method sequentially uses partial subgradient information and the…
Fast Proximal Gradient Methods for Nonsmooth Convex Optimization for Tomographic Image Reconstruction
Elias S. Helou, Marcelo V. W. Zibetti, Gabor T. Herman
The Fast Proximal Gradient Method (FPGM) and the Monotone FPGM (MFPGM) for minimization of nonsmooth convex functions are introduced and applied to tomographic image reconstruction…
Derivative-Free Superiorization: Principle and Algorithm
Yair Censor, Edgar Garduño, Elias S. Helou +1
The superiorization methodology is intended to work with input data of constrained minimization problems, that is, a target function and a set of constraints. However, it is based…
The Discrete Fourier Transform for Golden Angle Linogram Sampling
Elias S. Helou, Marcelo V. W. Zibetti, Leon Axel +3
Estimation of the Discrete-Time Fourier Transform (DTFT) at points of a finite domain arises in many imaging applications. A new approach to this task, the Golden Angle Linogram Fo…
Superiorization of Preconditioned Conjugate Gradient Algorithms for Tomographic Image Reconstruction
Elias S. Helou, Gabor T. Herman, Chuan Lin +1
Properties of Superiorized Preconditioned Conjugate Gradient (SupPCG) algorithms in image reconstruction from projections are examined. Least squares (LS) is usually chosen for mea…