Target-oriented SAR imaging for SCR improvement via deep MF-ADMM-Net
M Li, J Wu, W Huo, R Jiang, Z Li… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Synthetic aperture radar (SAR) is an important means for target surveillance through
reconstructing the microwave image of the observation area. However, under the condition …
reconstructing the microwave image of the observation area. However, under the condition …
Empirical Bayesian inference using a support informed prior
This paper develops a new empirical Bayesian inference algorithm for solving a linear
inverse problem given multiple measurement vectors of noisy observable data. Specifically …
inverse problem given multiple measurement vectors of noisy observable data. Specifically …
Sampling-based spotlight SAR image reconstruction from phase history data for speckle reduction and uncertainty quantification
Spotlight mode airborne synthetic aperture radar (SAR) is a coherent imaging modality that
is an important tool in remote sensing. Existing methods for spotlight SAR image …
is an important tool in remote sensing. Existing methods for spotlight SAR image …
Sequential edge detection using joint hierarchical Bayesian learning
This paper introduces a new sparse Bayesian learning (SBL) algorithm that jointly recovers
a temporal sequence of edge maps from noisy and under-sampled Fourier data. The new …
a temporal sequence of edge maps from noisy and under-sampled Fourier data. The new …
Fast and direct inversion methods for the multivariate nonequispaced fast Fourier transform
The well-known discrete Fourier transform (DFT) can easily be generalized to arbitrary
nodes in the spatial domain. The fast procedure for this generalization is referred to as …
nodes in the spatial domain. The fast procedure for this generalization is referred to as …
Sequential image recovery from noisy and under-sampled Fourier data
A new algorithm is developed to jointly recover a temporal sequence of images from noisy
and under-sampled Fourier data. Specifically we consider the case where each data set is …
and under-sampled Fourier data. Specifically we consider the case where each data set is …
[PDF][PDF] Accurate and efficient image reconstruction from multiple measurements of fourier samples
TS Gelb - Journal of Computational Mathematics, 2020 - par.nsf.gov
Several problems in imaging acquire multiple measurement vectors (MMVs) of Fourier
samples for the same underlying scene. Image recovery techniques from MMVs aim to …
samples for the same underlying scene. Image recovery techniques from MMVs aim to …
Detecting edges from non-uniform Fourier data via sparse Bayesian learning
In recent investigations, the problem of detecting edges given non-uniform Fourier data was
reformulated as a sparse signal recovery problem with an ℓ _1 ℓ 1-regularized least squares …
reformulated as a sparse signal recovery problem with an ℓ _1 ℓ 1-regularized least squares …
Synthetic aperture radar image formation with uncertainty quantification
V Churchill - 2020 - search.proquest.com
Synthetic aperture radar (SAR) is a day or night any-weather imaging modality that is an
important tool in remote sensing. Most existing SAR image formation methods result in a …
important tool in remote sensing. Most existing SAR image formation methods result in a …
Empirical bayesian inference using joint sparsity
This paper develops a new empirical Bayesian inference algorithm for solving a linear
inverse problem given multiple measurement vectors (MMV) of under-sampled and noisy …
inverse problem given multiple measurement vectors (MMV) of under-sampled and noisy …