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Backtracking Strategies for Accelerated Descent Methods with Smooth Composite Objectives
A backtracking strategy for a general Fast Iterative Shrinkage/Thresholding Algorithm which has been recently proposed in (Chambolle, Pock, 2016) for strongly convex objective functions is presented and accelerated convergence rates are proved.
Bilevel approaches for learning of variational imaging models
Newton type methods are studied for the solution of the problems at hand, combining them with sampling techniques in case of large databases, and the computational verification of the developed techniques is extensively documented.
Infimal Convolution of Data Discrepancies for Mixed Noise Removal
We consider the problem of image denoising in the presence of noise whose statistical properties are a combination of two different distributions. We focus on noise distributions frequently conside...
Graph Clustering, Variational Image Segmentation Methods and Hough Transform Scale Detection for Object Measurement in Images
- L. Calatroni, Y. V. Gennip, C. Schönlieb, Hannah M. Rowland, A. Flenner
- Computer ScienceJournal of Mathematical Imaging and Vision
- 27 February 2016
This work considers the problem of scale detection in images where a region of interest is present together with a measurement tool (e.g. a ruler) and focuses on the graph-based method presented in Bertozzi and Flenner which reinterprets classical continuous Ginzburg–Landau minimisation models in a totally discrete framework.
Anisotropic osmosis filtering for shadow removal in images
- S. Parisotto, L. Calatroni, M. Caliari, C. Schönlieb, J. Weickert
- Computer ScienceInverse Problems
- 17 September 2018
An anisotropic extension of the isotropic osmosis model that has been introduced by Weickert et al (2013 Energy Minimization Methods in Computer Vision and Pattern Recognition) for visual computing applications is presented, and it is shown that in the integrable setting, linearAnisotropic Osmosis minimises an energy that involves a suitable quadratic form which models local directional structures.
COL0RME: Covariance-Based l0 Super-Resolution Microscopy with Intensity Estimation
- V. Stergiopoulou, J. H. D. M. Goulart, S. Schaub, L. Calatroni, L. Blanc-Féraud
- Computer ScienceIEEE 18th International Symposium on Biomedical…
- 26 October 2020
The method COL0RME is presented, which codifies the assumption of sparse distribution of the fluorescent molecules as well as the temporal and spatial independence between emitters via a non-convex optimization problem formulated in the covariance domain, and estimates background and noise statistics.
A Flexible Space-Variant Anisotropic Regularization for Image Restoration with Automated Parameter Selection
Several numerical results showing significant quality-improvement of the proposed model with respect to some related state-of-the-art competitors are reported, in particular in terms of texture and detail preservation.
Visual illusions via neural dynamics: Wilson-Cowan-type models and the efficient representation principle.
- M. Bertalmío, L. Calatroni, Valentina Franceschi, B. Franceschiello, Alexander Gomez Villa, D. Prandi
- BiologyJournal of neurophysiology
- 30 July 2019
This work formally proves that there can't be an energy functional that the Wilson-Cowan equations are minimizing, but that a slight modification makes them variational and yields a model that is consistent with the efficient representation principle.
A Scaled and Adaptive FISTA Algorithm for Signal-Dependent Sparse Image Super-Resolution Problems