Bayesian compressive sensing using Laplace priors
SD Babacan, R Molina… - IEEE Transactions on …, 2009 - ieeexplore.ieee.org
In this paper, we model the components of the compressive sensing (CS) problem, ie, the
signal acquisition process, the unknown signal coefficients and the model parameters for the …
signal acquisition process, the unknown signal coefficients and the model parameters for the …
Variational Bayesian blind image deconvolution: A review
In this paper we provide a review of the recent literature on Bayesian Blind Image
Deconvolution (BID) methods. We believe that two events have marked the recent history of …
Deconvolution (BID) methods. We believe that two events have marked the recent history of …
Variational Bayesian super resolution
SD Babacan, R Molina… - IEEE Transactions on …, 2010 - ieeexplore.ieee.org
In this paper, we address the super resolution (SR) problem from a set of degraded low
resolution (LR) images to obtain a high resolution (HR) image. Accurate estimation of the …
resolution (LR) images to obtain a high resolution (HR) image. Accurate estimation of the …
Blind and semi-blind deblurring of natural images
MSC Almeida, LB Almeida - IEEE Transactions on image …, 2009 - ieeexplore.ieee.org
A method for blind image deblurring is presented. The method only makes weak
assumptions about the blurring filter and is able to undo a wide variety of blurring …
assumptions about the blurring filter and is able to undo a wide variety of blurring …
Softcuts: a soft edge smoothness prior for color image super-resolution
Designing effective image priors is of great interest to image super-resolution (SR), which is
a severely under-determined problem. An edge smoothness prior is favored since it is able …
a severely under-determined problem. An edge smoothness prior is favored since it is able …
Regularization parameter selection for nonlinear iterative image restoration and MRI reconstruction using GCV and SURE-based methods
S Ramani, Z Liu, J Rosen, JF Nielsen… - IEEE Transactions on …, 2012 - ieeexplore.ieee.org
Regularized iterative reconstruction algorithms for imaging inverse problems require
selection of appropriate regularization parameter values. We focus on the challenging …
selection of appropriate regularization parameter values. We focus on the challenging …
Variational Bayesian blind deconvolution using a total variation prior
SD Babacan, R Molina… - IEEE Transactions on …, 2008 - ieeexplore.ieee.org
In this paper, we present novel algorithms for total variation (TV) based blind deconvolution
and parameter estimation utilizing a variational framework. Using a hierarchical Bayesian …
and parameter estimation utilizing a variational framework. Using a hierarchical Bayesian …
Parameter selection for total-variation-based image restoration using discrepancy principle
There are two key issues in successfully solving the image restoration problem: 1)
estimation of the regularization parameter that balances data fidelity with the regularity of the …
estimation of the regularization parameter that balances data fidelity with the regularity of the …
Maximum a Posteriori Video Super-Resolution Using a New Multichannel Image Prior
SP Belekos, NP Galatsanos… - IEEE transactions on …, 2010 - ieeexplore.ieee.org
Super-resolution (SR) is the term used to define the process of estimating a high-resolution
(HR) image or a set of HR images from a set of low-resolution (LR) observations. In this …
(HR) image or a set of HR images from a set of low-resolution (LR) observations. In this …
Variational Bayesian method for retinex
L Wang, L Xiao, H Liu, Z Wei - IEEE Transactions on Image …, 2014 - ieeexplore.ieee.org
In this paper, we propose a variational Bayesian method for Retinex to simulate and
interpret how the human visual system perceives color. To construct a hierarchical Bayesian …
interpret how the human visual system perceives color. To construct a hierarchical Bayesian …