Residual whiteness principle for automatic parameter selection in $\ell_2$-$\ell_2$ image super-resolution problems
Numerical Analysis
2021-04-05 v1 Numerical Analysis
Abstract
We propose an automatic parameter selection strategy for variational image super-resolution of blurred and down-sampled images corrupted by additive white Gaussian noise (AWGN) with unknown standard deviation. By exploiting particular properties of the operators describing the problem in the frequency domain, our strategy selects the optimal parameter as the one optimising a suitable residual whiteness measure. Numerical tests show the effectiveness of the proposed strategy for generalised - Tikhonov problems.
Keywords
Cite
@article{arxiv.2104.01001,
title = {Residual whiteness principle for automatic parameter selection in $\ell_2$-$\ell_2$ image super-resolution problems},
author = {Monica Pragliola and Luca Calatroni and Alessandro Lanza and Fiorella Sgallari},
journal= {arXiv preprint arXiv:2104.01001},
year = {2021}
}