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High angle annular dark field (HAADF)-scanning transmission electron microscope (STEM) data is increasingly being used in the physical sciences to research materials in 3D because it reduces the effects of Bragg diffraction seen in bright field TEM data. Typically, tomographic reconstructions are performed by directly applying either filtered back projection (FBP) or the simultaneous iterative reconstruction...
While Markov random field (MRF) models have been widely used in the solution of inverse problems, a major disadvantage of these models is the difficulty of parameter estimation. At its root, this parameter estimation problem stems from the inability to explicitly express the joint distribution of an MRF in terms of the conditional distributions of elements given their neighbors. The objective of this...
This paper addresses two issues related to the detection of hyperspectral anomalies. The first issue is the evaluation of anomaly detector performance even when labeled data is not available. The second issue is the estimation of the covariance structure of the data in local detection methods, such as the RX detector, when the number of available training pixels n is not much larger than (and may...
Regression from high dimensional observation vectors is particularly difficult when training data is limited. More specifically, if the number of sample vectors n is less than dimension of the sample vectors p, then accurate regression is difficult to perform without prior knowledge of the data covariance. In this paper, we propose a novel approach to high dimensional regression for application when...
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