17 citations · 21 across the 8 of their papers we have counts for
9 papers
Whiteness-based bilevel estimation of weighted TV parameter maps for image denoising
Monica Pragliola, Luca Calatroni, Alessandro Lanza
We consider a bilevel optimisation strategy based on normalised residual whiteness loss for estimating the weighted total variation parameter maps for denoising images corrupted by…
Whiteness-based bilevel learning of regularization parameters in imaging
Carlo Santambrogio, Monica Pragliola, Alessandro Lanza +2
We consider an unsupervised bilevel optimization strategy for learning regularization parameters in the context of imaging inverse problems in the presence of additive white Gaussi…
Bilevel learning of regularization models and their discretization for image deblurring and super-resolution
Tatiana A. Bubba, Luca Calatroni, Ambra Catozzi +6
Bilevel learning is a powerful optimization technique that has extensively been employed in recent years to bridge the world of model-driven variational approaches with data-driven…
ADMM-based residual whiteness principle for automatic parameter selection in super-resolution problems
Monica Pragliola, Luca Calatroni, Alessandro Lanza +1
We propose an automatic parameter selection strategy for the problem of image super-resolution for images corrupted by blur and additive white Gaussian noise with unknown standard…
On and beyond Total Variation regularisation in imaging: the role of space variance
Monica Pragliola, Luca Calatroni, Alessandro Lanza +1
Over the last 30 years a plethora of variational regularisation models for image reconstruction has been proposed and thoroughly inspected by the applied mathematics community. Amo…
Residual whiteness principle for automatic parameter selection in - image super-resolution problems
Monica Pragliola, Luca Calatroni, Alessandro Lanza +1
We propose an automatic parameter selection strategy for variational image super-resolution of blurred and down-sampled images corrupted by additive white Gaussian noise (AWGN) wit…
Space-adaptive anisotropic bivariate Laplacian regularization for image restoration
Luca Calatroni, Alessandro Lanza, Monica Pragliola +1
In this paper we present a new regularization term for variational image restoration which can be regarded as a space-variant anisotropic extension of the classical isotropic Total…
Adaptive parameter selection for weighted-TV image reconstruction problems
Luca Calatroni, Alessandro Lanza, Monica Pragliola +1
We propose an efficient estimation technique for the automatic selection of locally-adaptive Total Variation regularisation parameters based on an hybrid strategy which combines a…
A flexible space-variant anisotropic regularisation for image restoration with automated parameter selection
Luca Calatroni, Alessandro Lanza, Monica Pragliola +1
We propose a new space-variant anisotropic regularisation term for variational image restoration, based on the statistical assumption that the gradients of the target image distrib…