no code implementations • 31 May 2023 • Davide Evangelista, Elena Morotti, Elena Loli Piccolomini, James Nagy
Numerical experiments are performed to verify the accuracy and stability of the proposed approaches for image deblurring when unknown or not-quantified noise is present; the results confirm that they improve the network stability with respect to noise.
2 code implementations • 24 Nov 2022 • Davide Evangelista, James Nagy, Elena Morotti, Elena Loli Piccolomini
The solution of linear inverse problems arising, for example, in signal and image processing is a challenging problem since the ill-conditioning amplifies, in the solution, the noise present in the data.
no code implementations • 4 Jan 2021 • Chao Wang, Min Tao, Chen-Nee Chuah, James Nagy, Yifei Lou
Consequently, we postulate that applying L1/L2 on the gradient is better than the classic total variation (the L1 norm on the gradient) to enforce the sparsity of the image gradient.
no code implementations • 31 May 2020 • Chao Wang, Min Tao, James Nagy, Yifei Lou
In this paper, we consider minimizing the L1/L2 term on the gradient for a limited-angle scanning problem in computed tomography (CT) reconstruction.
1 code implementation • 28 May 2017 • James Herring, James Nagy, Lars Ruthotto
LAP is most promising for cases when the subproblem corresponding to one of the variables is considerably easier to solve than the other.