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02/20/2023
Bilevel learning of regularization models and their discretization for image deblurring and super-resolution
Bilevel learning is a powerful optimization technique that has extensive...
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07/21/2022
Whiteness-based parameter selection for Poisson data in variational image processing
We propose a novel automatic parameter selection strategy for variationa...
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05/26/2022
Automatic parameter selection for the TGV regularizer in image restoration under Poisson noise
We address the image restoration problem under Poisson noise corruption....
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08/30/2021
ADMM-based residual whiteness principle for automatic parameter selection in super-resolution problems
We propose an automatic parameter selection strategy for the problem of ...
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04/08/2021
On and beyond Total Variation regularisation in imaging: the role of space variance
Over the last 30 years a plethora of variational regularisation models f...
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04/02/2021
Residual whiteness principle for automatic parameter selection in ℓ_2-ℓ_2 image super-resolution problems
We propose an automatic parameter selection strategy for variational ima...
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06/24/2020
Overcomplete representation in a hierarchical Bayesian framework
A common task in inverse problems and imaging is finding a solution that...
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03/14/2020
Sparsity promoting hybrid solvers for hierarchical Bayesian inverse problems
The recovery of sparse generative models from few noisy measurements is ...
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03/14/2020
Hybrid solver for hierarchical Bayesian inverse problems
The recovery of sparse generative models from few noisy measurements is ...
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08/02/2019
Space-adaptive anisotropic bivariate Laplacian regularization for image restoration
In this paper we present a new regularization term for variational image...
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06/21/2019
