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Hyperspectral image reconstruction from random projections on GPU
Sevilla, Jorge; Martin, Gabriel; Nascimento, Jose; Bioucas-Dias, JoséHyperspectral data compression and dimensionality reduction has received considerable interest in recent years due to the high spectral resolution of these images. Contrarily to the conventional dimensionality reduction schemes, the spectral compressive acquisition method (SpeCA) performs dimensionality reduction based on random projections. The SpeCA methodology has applications in Hyperspectral Compressive Se...
GPU implementation of a hyperspectral coded aperture algorithm for compressive ...
Bernabe, Sergio; Martin, Gabriel; Nascimento, Jose; Bioucas-Dias, José; Plaza, Antonio; Silva, VítorThis paper presents a new parallel implementation of a previously hyperspectral coded aperture (HYCA) algorithm for compressive sensing on graphics processing units (GPUs). HYCA method combines the ideas of spectral unmixing and compressive sensing exploiting the high spatial correlation that can be observed in the data and the generally low number of endmembers needed in order to explain the data. The proposed...
Phase Drift Estimation and Symbol Detection in Digital Communications: A Stocha...
Bioucas-Dias, José; Dinis, Rui; Pedrosa, Pedro; Nunes, FernandoThis paper proposes a novel Bayesian stochastic filtering approach for the simultaneous phase drift estimation and symbol detection in digital communications. The posterior density of the phase drift is propagated in a recursive fashion by implementing a prediction and a filtering step in each iteration. The prediction step is supported on a random walk model playing the role of prior for the phase drift proces...
CAPE: combinatorial absolute phase estimation
Valadão, Gonçalo; Bioucas-Dias, JoséAn absolute phase estimation algorithm for interferometric applications is introduced. The approach is Bayesian. Besides coping with the 2π-periodic sinusoidal nonlinearity in the observations, the proposed methodology assumes a first-order Markov random field prior and a maximum a posteriori probability (MAP) viewpoint. For computing the MAP solution, we provide a combinatorial suboptimal algorithm that involv...
Phase Unwrapping via Graph Cuts
Bioucas-Dias, José; Valadão, GonçaloPhase unwrapping is the inference of absolute phase from modulo-2pi phase. This paper introduces a new energy minimization framework for phase unwrapping. The considered objective functions are first-order Markov random fields. We provide an exact energy minimization algorithm, whenever the corresponding clique potentials are convex, namely for the phase unwrapping classical Lp norm, with pges1. Its complexity ...