no code implementations • 9 Jul 2018 • Milad Niknejad, Jose M. Bioucas-Dias, Mario A. T. Figueiredo
This paper proposes a general framework for internal patch-based image restoration based on Conditional Random Fields (CRF).
no code implementations • 9 Jul 2018 • Milad Niknejad, Jose M. Bioucas-Dias, Mario A. T. Figueiredo
This paper introduces a new approach to patch-based image restoration based on external datasets and importance sampling.
1 code implementation • 12 Apr 2018 • Amirhossein Javaheri, Hadi Zayyani, Mario A. T. Figueiredo, Farrokh Marvasti
In this paper, we exploit a Continuous Mixed Norm (CMN) for robust sparse recovery instead of $\ell_p$-norm.
no code implementations • 1 Mar 2018 • Milad Niknejad, Mario A. T. Figueiredo
In this paper, we address the problem of denoising images degraded by Poisson noise.
no code implementations • ICCV 2017 • Matteo Denitto, Simone Melzi, Manuele Bicego, Umberto Castellani, Alessandro Farinelli, Mario A. T. Figueiredo, Yanir Kleiman, Maks Ovsjanikov
This problem statement is similar to that of "biclustering", implying that RBC can be cast as a biclustering problem.
no code implementations • 21 Jun 2017 • Milad Niknejad, Jose M. Bioucas-Dias, Mario A. T. Figueiredo
In this paper, we propose a new image denoising method, tailored to specific classes of images, assuming that a dataset of clean images of the same class is available.
no code implementations • 9 Jun 2017 • Milad Niknejad, Jose M. Bioucas-Dias, Mario A. T. Figueiredo
In this paper, we address the problem of recovering images degraded by Poisson noise, where the image is known to belong to a specific class.
no code implementations • CVPR 2017 • Zheng Xu, Mario A. T. Figueiredo, Xiaoming Yuan, Christoph Studer, Tom Goldstein
Relaxed ADMM is a generalization of ADMM that often achieves better performance, but its efficiency depends strongly on algorithm parameters that must be chosen by an expert user.
no code implementations • 20 Feb 2017 • Mario A. T. Figueiredo
This paper shows that there is another analysis vs synthesis dichotomy, in terms of how the whole image is related to the patches, and that all existing patch-based formulations that provide a global image prior belong to the analysis category.
no code implementations • 24 May 2016 • Zheng Xu, Mario A. T. Figueiredo, Tom Goldstein
The alternating direction method of multipliers (ADMM) is a versatile tool for solving a wide range of constrained optimization problems, with differentiable or non-differentiable objective functions.
no code implementations • 14 Sep 2014 • Mario A. T. Figueiredo, Robert D. Nowak
This paper studies ordered weighted L1 (OWL) norm regularization for sparse estimation problems with strongly correlated variables.