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An Extension of Averaged-Operator-Based Algorithms
Miguel Simões, José Bioucas-Dias, Luis B. Almeida
Many of the algorithms used to solve minimization problems with sparsity-inducing regularizers are generic in the sense that they do not take into account the sparsity of the solut…
Robust Collaborative Nonnegative Matrix Factorization For Hyperspectral Unmixing (R-CoNMF)
Jun Li, Jose M. Bioucas-Dias, Antonio Plaza +1
The recently introduced collaborative nonnegative matrix factorization (CoNMF) algorithm was conceived to simultaneously estimate the number of endmembers, the mixing matrix, and t…
Alternating Direction Algorithms for Constrained Sparse Regression: Application to Hyperspectral Unmixing
José M. Bioucas-Dias, Mário A. T. Figueiredo
Convex optimization problems are common in hyperspectral unmixing. Examples include: the constrained least squares (CLS) and the fully constrained least squares (FCLS) problems, wh…
Restoration of Poissonian Images Using Alternating Direction Optimization
Mário A. T. Figueiredo, José M. Bioucas-Dias
Much research has been devoted to the problem of restoring Poissonian images, namely for medical and astronomical applications. However, the restoration of these images using state…
An Augmented Lagrangian Approach to the Constrained Optimization Formulation of Imaging Inverse Problems
Manya V. Afonso, José M. Bioucas-Dias, Mário A. T. Figueiredo
We propose a new fast algorithm for solving one of the standard approaches to ill-posed linear inverse problems (IPLIP), where a (possibly non-smooth) regularizer is minimized unde…
Multiplicative Noise Removal Using Variable Splitting and Constrained Optimization
José M. Bioucas-Dias, Mário A. T. Figueiredo
Multiplicative noise (also known as speckle noise) models are central to the study of coherent imaging systems, such as synthetic aperture radar and sonar, and ultrasound and laser…