TGV-based restoration of Poissonian images with automatic estimation of the regularization parameter

04/29/2021
by   Daniela di Serafino, et al.
0

The problem of restoring images corrupted by Poisson noise is common in many application fields and, because of its intrinsic ill posedness, it requires regularization techniques for its solution. The effectiveness of such techniques depends on the value of the regularization parameter balancing data fidelity and regularity of the solution. Here we consider the Total Generalized Variation regularization introduced in [SIAM J. Imag. Sci, 3(3), 492-526, 2010], which has demonstrated its ability of preserving sharp features as well as smooth transition variations, and introduce an automatic strategy for defining the value of the regularization parameter. We solve the corresponding optimization problem by using a 3-block version of ADMM. Preliminary numerical experiments support the proposed approach.

READ FULL TEXT
research
06/29/2022

Automatic balancing parameter selection for Tikhonov-TV regularization

This paper considers large-scale linear ill-posed inverse problems whose...
research
05/26/2022

Automatic parameter selection for the TGV regularizer in image restoration under Poisson noise

We address the image restoration problem under Poisson noise corruption....
research
04/30/2021

Directional TGV-based image restoration under Poisson noise

We are interested in the restoration of noisy and blurry images where th...
research
11/18/2021

Identification of the Source for Full Parabolic Equations

In this work, we consider the problem of identifying the time independen...
research
05/06/2020

Projected Newton method for noise constrained ℓ_p regularization

Choosing an appropriate regularization term is necessary to obtain a mea...
research
06/16/2015

Post-Reconstruction Deconvolution of PET Images by Total Generalized Variation Regularization

Improving the quality of positron emission tomography (PET) images, affe...
research
08/30/2021

ADMM-based residual whiteness principle for automatic parameter selection in super-resolution problems

We propose an automatic parameter selection strategy for the problem of ...

Please sign up or login with your details

Forgot password? Click here to reset