A Primal-Dual Approach for a Total Variation Wasserstein Flow. - Martin Benning; Luca Calatroni; Bertram Düring; Carola-Bibiane Schönlieb (GSI, 2013)

Dynamic Sampling Schemes for Optimal Noise Learning Under Multiple Nonsmooth Constraints. - Luca Calatroni; Juan Carlos de los Reyes; Carola-Bibiane Schönlieb (System Modelling and Optimization, 2013)

Bilevel approaches for learning of variational imaging models. - Luca Calatroni; Cao Chung; Juan Carlos de los Reyes; Carola-Bibiane Schönlieb; Tuomo Valkonen (CoRR, 2015)

Graph Clustering, Variational Image Segmentation Methods and Hough Transform Scale Detection for Object Measurement in Images. - Luca Calatroni; Yves van Gennip; Carola-Bibiane Schönlieb; Hannah M. Rowland; Arjuna Flenner (J. Math. Imaging Vis., 2017)

Infimal Convolution of Data Discrepancies for Mixed Noise Removal. - Luca Calatroni; Juan Carlos de los Reyes; Carola-Bibiane Schönlieb (SIAM J. Imaging Sci., 2017)

Digital Cultural Heritage Imaging via Osmosis Filtering. - Simone Parisotto; Luca Calatroni; Claudia Daffara (ICISP, 2018)

Unveiling the invisible - mathematical methods for restoring and interpreting illuminated manuscripts. - Luca Calatroni; Marie d'Autume; Rob Hocking; Stella Panayotova; Simone Parisotto; Paola Ricciardi; Carola-Bibiane Schönlieb (CoRR, 2018)

A Cortical-Inspired Model for Orientation-Dependent Contrast Perception: A Link with Wilson-Cowan Equations. - Marcelo Bertalmío; Luca Calatroni; Valentina Franceschi; Benedetta Franceschiello; Dario Prandi (SSVM, 2019)

Space-adaptive anisotropic bivariate Laplacian regularization for image restoration. - Luca Calatroni; Alessandro Lanza; Monica Pragliola; Fiorella Sgallari (CoRR, 2019)

A Flexible Space-Variant Anisotropic Regularization for Image Restoration with Automated Parameter Selection. - Luca Calatroni; Alessandro Lanza; Monica Pragliola; Fiorella Sgallari (SIAM J. Imaging Sci., 2019)

Backtracking Strategies for Accelerated Descent Methods with Smooth Composite Objectives. - Luca Calatroni; Antonin Chambolle (SIAM J. Optim., 2019)

On the inverse Potts functional for single-image super-resolution problems. - Pasquale Cascarano; Luca Calatroni; Elena Loli Piccolomini (CoRR, 2020)

Weighted-CEL0 sparse regularisation for molecule localisation in super-resolution microscopy with Poisson data. - Marta Lazzaretti; Luca Calatroni; Claudio Estatico (CoRR, 2020)

Variational Osmosis for Non-Linear Image Fusion. - Simone Parisotto; Luca Calatroni; Aurélie Bugeau; Nicolas Papadakis; Carola-Bibiane Schönlieb (IEEE Trans. Image Process., 2020)

A scaled, inexact and adaptive Fast Iterative Soft-Thresholding Algorithm for convex image restoration. - Luca Calatroni; Simone Rebegoldi (ICCSA (Workshops), 2021)

A continuous, non-convex & sparse super-resolution approach for fluorescence microscopy data with Poisson noise. - Marta Lazzaretti; Luca Calatroni; Claudio Estatico (ICCSA (Workshops), 2021)

Weighted-Celo Sparse Regularisation For Molecule Localisation In Super-Resolution Microscopy With Poisson Data. - Marta Lazzaretti; Luca Calatroni; Claudio Estatico (ISBI, 2021)

Non-Convex Super-Resolution Of Oct Images Via Sparse Representation. - Gabriele Scrivanti; Luca Calatroni; Serena Morigi; Lindsay Nicholson; Alin Achim (ISBI, 2021)

COL0RME: Covariance-Based l0 Super-Resolution Microscopy with Intensity Estimation. - Vasiliki Stergiopoulou; José Henrique de Morais Goulart; Sébastien Schaub; Luca Calatroni; Laure Blanc-Féraud (ISBI, 2021)

A Scaled and Adaptive FISTA Algorithm for Signal-Dependent Sparse Image Super-Resolution Problems. - Marta Lazzaretti; Simone Rebegoldi; Luca Calatroni; Claudio Estatico (SSVM, 2021)

Residual Whiteness Principle for Automatic Parameter Selection in ℓ 2-ℓ 2 Image Super-Resolution Problems. - Monica Pragliola; Luca Calatroni; Alessandro Lanza; Fiorella Sgallari (SSVM, 2021)

On and beyond Total Variation regularisation in imaging: the role of space variance. - Monica Pragliola; Luca Calatroni; Alessandro Lanza; Fiorella Sgallari (CoRR, 2021)

Mathematical osmosis imaging for multi-modal and multi-spectral applications in Cultural Heritage conservation. - Simone Parisotto; Luca Calatroni; Claudia Daffara (CoRR, 2021)

ADMM-based residual whiteness principle for automatic parameter selection in super-resolution problems. - Monica Pragliola; Luca Calatroni; Alessandro Lanza; Fiorella Sgallari (CoRR, 2021)

A Cortical-Inspired Sub-Riemannian Model for Poggendorff-Type Visual Illusions. - Emre Baspinar; Luca Calatroni; Valentina Franceschi; Dario Prandi (J. Imaging, 2021)

Cortical-Inspired Wilson-Cowan-Type Equations for Orientation-Dependent Contrast Perception Modelling. - Marcelo Bertalmío; Luca Calatroni; Valentina Franceschi; Benedetta Franceschiello; Dario Prandi (J. Math. Imaging Vis., 2021)

Accelerated Iterative Regularization via Dual Diagonal Descent. - Luca Calatroni; Guillaume Garrigos; Lorenzo Rosasco; Silvia Villa (SIAM J. Optim., 2021)

Efficient $ ell ^0$ Gradient-Based Super-Resolution for Simplified Image Segmentation. - Pasquale Cascarano; Luca Calatroni; Elena Loli Piccolomini (IEEE Trans. Computational Imaging, 2021)

3D Image Super-Resolution by Fluorophore Fluctuations and MA-TIRF Microscopy Reconstruction (3D-COL0RME). - Vasiliki Stergiopoulou; Luca Calatroni; Sébastien Schaub; Laure Blanc-Féraud (ISBI, 2022)

Constrained and Unconstrained Inverse Potts Modelling for Joint Image Super-Resolution and Segmentation. - Dario Mylonopoulos; Pasquale Cascarano; Luca Calatroni; Elena Loli Piccolomini (Image Process. Line, 2022)

Modular-Proximal Gradient Algorithms in Variable Exponent Lebesgue Spaces. - Marta Lazzaretti; Luca Calatroni; Claudio Estatico (SIAM J. Sci. Comput., 2022)

Scaled, Inexact, and Adaptive Generalized FISTA for Strongly Convex Optimization. - Simone Rebegoldi; Luca Calatroni (SIAM J. Optim., 2022)

Stochastic Gradient Descent for Linear Inverse Problems in Variable Exponent Lebesgue Spaces. - Marta Lazzaretti; Zeljko Kereta; Claudio Estatico; Luca Calatroni (SSVM, 2023)

Fluctuation-Based Deconvolution in Fluorescence Microscopy Using Plug-and-Play Denoisers. - Vasiliki Stergiopoulou; Subhadip Mukherjee; Luca Calatroni; Laure Blanc-Féraud (SSVM, 2023)

Bilevel learning of regularization models and their discretization for image deblurring and super-resolution. - Tatiana A. Bubba; Luca Calatroni; Ambra Catozzi; Serena Crisci; Thomas Pock; Monica Pragliola; Siiri Rautio; Danilo Riccio; Andrea Sebastiani (CoRR, 2023)

Deep image prior inpainting of ancient frescoes in the Mediterranean Alpine arc. - Fabio Merizzi; Perrine Saillard; Oceane Acquier; Elena Morotti; Elena Loli Piccolomini; Luca Calatroni; Rosa Maria Dessì (CoRR, 2023)

A mobility-SAV approach for a Cahn-Hilliard equation with degenerate mobilities. - Elie Bretin; Luca Calatroni; Simon Masnou (CoRR, 2023)

Beyond ℓ1 sparse coding in V1. - Ilias Rentzeperis; Luca Calatroni; Laurent U. Perrinet; Dario Prandi (PLoS Comput. Biol., 2023)

Space-variant image reconstruction via Cauchy regularisation: Application to Optical Coherence Tomography. - Alin Achim; Luca Calatroni; Serena Morigi; Gabriele Scrivanti (Signal Process., 2023)

A Unified Surface Geometric Framework for Feature-Aware Denoising, Hole Filling and Context-Aware Completion. - Luca Calatroni; Martin Huska; Serena Morigi; Giuseppe Antonio Recupero (J. Math. Imaging Vis., 2023)

ADMM-Based Residual Whiteness Principle for Automatic Parameter Selection in Single Image Super-Resolution Problems. - Monica Pragliola; Luca Calatroni; Alessandro Lanza; Fiorella Sgallari (J. Math. Imaging Vis., 2023)

Fast and stable schemes for non-linear osmosis filtering. - Luca Calatroni; Serena Morigi; Simone Parisotto; Giuseppe Antonio Recupero (Comput. Math. Appl., 2023)

On and Beyond Total Variation Regularization in Imaging: The Role of Space Variance. - Monica Pragliola; Luca Calatroni; Alessandro Lanza; Fiorella Sgallari (SIAM Rev., 2023)

Whiteness-Based Bilevel Learning of Regularization Parameters in Imaging. - Carlo Santambrogio; Monica Pragliola; Alessandro Lanza; Marco Donatelli; Luca Calatroni (EUSIPCO, 2024)

Physics-Inspired Generative Adversarial Modelling for Fluctuation-Based Super-Resolution Microscopy. - Hamza Mentagui; Luca Calatroni; Sébastien Schaub; Laure Blanc-Féraud (ISBI, 2024)

On $ ell_{0}$ Bregman-Relaxations for Kullback-Leibler Sparse Regressionx. - M'hamed Essafri; Luca Calatroni; Emmanuel Soubies (MLSP, 2024)

Algorithmic unfolding for image reconstruction and localization problems in fluorescence microscopy. - Silvia Bonettini; Luca Calatroni; Danilo Pezzi; Marco Prato (CoRR, 2024)

Parameter-Free FISTA by Adaptive Restart and Backtracking. - Jean-François Aujol; Luca Calatroni; Charles Dossal; Hippolyte Labarrière; Aude Rondepierre (SIAM J. Optim., 2024)

Guest Editorial JMIV Special Issue SSVM'23. - Luca Calatroni; Marco Donatelli; Serena Morigi; Marco Prato; Matteo Santacesaria (J. Math. Imaging Vis., 2024)

Whiteness-Based Bilevel Estimation of Weighted TV Parameter Maps for Image Denoising. - Monica Pragliola; Luca Calatroni; Alessandro Lanza (SSVM (1), 2025)

Learning Spatially Adaptive ℓ1-Norms Weights for Convolutional Synthesis Regularization. - Andreas Kofler; Luca Calatroni; Christoph Kolbitsch; Kostas Papafitsoros (CoRR, 2025)

Patch-based learning of adaptive Total Variation parameter maps for blind image denoising. - Claudio Fantasia; Luca Calatroni; Xavier Descombes; Rim Rekik (CoRR, 2025)

Off-the-grid regularisation for Poisson inverse problems. - Marta Lazzaretti; Claudio Estatico; Alejandro Melero Carrillo; Luca Calatroni (Comput. Optim. Appl., 2025)

Deep Equilibrium models for Poisson Imaging Inverse problems via Mirror Descent. - Christian Daniele; Silvia Villa; Samuel Vaiter; Luca Calatroni (CoRR, 2025)