[HTML][HTML] A non-convex denoising model for impulse and Gaussian noise mixture removing using bi-level parameter identification
We propose a new variational framework to remove a mixture of Gaussian and impulse
noise from images. This framework is based on a non-convex PDE-constrained with a …
noise from images. This framework is based on a non-convex PDE-constrained with a …
An optimal control approach for determining the source term in fractional diffusion equation by different cost functionals
This work is devoted to the mathematical analysis of an inverse source problem governed by
a time-fractional diffusion equation. The aims of this paper are to identify the source function …
a time-fractional diffusion equation. The aims of this paper are to identify the source function …
A weighted parameter identification PDE-constrained optimization for inverse image denoising problem
This paper treats the inverse denoising problem which aims to compute simultaneously the
clean image and the weighting parameter λ. The formulated denoising problem is posed …
clean image and the weighting parameter λ. The formulated denoising problem is posed …
A denoising model adapted for impulse and Gaussian noises using a constrained-PDE
In denoising problems, it is always hard to deal with a mixture of two noise densities. In this
paper, we introduce a nonlinear constrained-PDE based on the fractional order tensor …
paper, we introduce a nonlinear constrained-PDE based on the fractional order tensor …
Primal-dual extragradient methods for nonlinear nonsmooth PDE-constrained optimization
C Clason, T Valkonen - SIAM Journal on Optimization, 2017 - SIAM
We study the extension of the Chambolle--Pock primal-dual algorithm to nonsmooth
optimization problems involving nonlinear operators between function spaces. Local …
optimization problems involving nonlinear operators between function spaces. Local …
A novel image denoising approach based on a non-convex constrained PDE: application to ultrasound images
In this paper, we are interested in the mathematical and simulation study of a new non-
convex constrained PDE to remove the mixture of Gaussian–impulse noise densities. The …
convex constrained PDE to remove the mixture of Gaussian–impulse noise densities. The …
An automatic L1-based regularization method for the analysis of FFC dispersion profiles with quadrupolar peaks
Abstract Fast Field-Cycling Nuclear Magnetic Resonance relaxometry is a non-destructive
technique to investigate molecular dynamics and structure of systems having a wide range …
technique to investigate molecular dynamics and structure of systems having a wide range …
An alternative extrapolation scheme of PDHGM for saddle point problem with nonlinear function
Primal-dual hybrid gradient (PDHG) method is a canonical and popular prototype for solving
saddle point problem (SPP). However, the nonlinear coupling term in SPP excludes the …
saddle point problem (SPP). However, the nonlinear coupling term in SPP excludes the …
L∞ fitting for inverse problems with uniform noise
C Clason - Inverse Problems, 2012 - iopscience.iop.org
For inverse problems where the data are corrupted by uniform noise such as arising from
quantization errors, the L∞ norm is a more robust data-fitting term than the standard L 2 …
quantization errors, the L∞ norm is a more robust data-fitting term than the standard L 2 …
Statistical inverse learning problems with random observations
We provide an overview of recent progress in statistical inverse problems with random
experimental design, covering both linear and nonlinear inverse problems. Different …
experimental design, covering both linear and nonlinear inverse problems. Different …