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Jose M. Bioucas-Dias

Researcher at Instituto Superior Técnico

Publications -  327
Citations -  32120

Jose M. Bioucas-Dias is an academic researcher from Instituto Superior Técnico. The author has contributed to research in topics: Hyperspectral imaging & Augmented Lagrangian method. The author has an hindex of 65, co-authored 326 publications receiving 27010 citations. Previous affiliations of Jose M. Bioucas-Dias include Southwestern University of Finance and Economics & IT University.

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Hyperspectral Unmixing Overview: Geometrical, Statistical, and Sparse Regression-Based Approaches

TL;DR: This paper presents an overview of un Mixing methods from the time of Keshava and Mustard's unmixing tutorial to the present, including Signal-subspace, geometrical, statistical, sparsity-based, and spatial-contextual unmixed algorithms.
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A New TwIST: Two-Step Iterative Shrinkage/Thresholding Algorithms for Image Restoration

TL;DR: This paper introduces two-step 1ST (TwIST) algorithms, exhibiting much faster convergence rate than 1ST for ill-conditioned problems, and introduces a monotonic version of TwIST (MTwIST); although the convergence proof does not apply, the effectiveness of the new methods are experimentally confirmed on problems of image deconvolution and of restoration with missing samples.
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Hyperspectral Remote Sensing Data Analysis and Future Challenges

TL;DR: A tutorial/overview cross section of some relevant hyperspectral data analysis methods and algorithms, organized in six main topics: data fusion, unmixing, classification, target detection, physical parameter retrieval, and fast computing.
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Fast Image Recovery Using Variable Splitting and Constrained Optimization

TL;DR: A new fast algorithm for solving one of the standard formulations of image restoration and reconstruction which consists of an unconstrained optimization problem where the objective includes an l2 data-fidelity term and a nonsmooth regularizer is proposed.