Color image restoration by filtering methods: a review
Digital images are corrupted with noise, and image denoising is an important step in image
processing modules. In this review, the latest developments in filtering methods for color …
processing modules. In this review, the latest developments in filtering methods for color …
[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 …
[HTML][HTML] A non-convex pde-constrained denoising model for impulse and gaussian noise mixture reduction
This paper introduces a novel optimization procedure to reduce a mixture of Gaussian and
impulse noise from images. This framework is based on a non-convex PDE-constrained with …
impulse noise from images. This framework is based on a non-convex PDE-constrained with …
Image denoising based on a variable spatially exponent PDE
A Laghrib, L Afraites - Applied and Computational Harmonic Analysis, 2024 - Elsevier
Image denoising is always considered an important area of image processing. In this work,
we address a new PDE-based model for image denoising that have been contaminated by …
we address a new PDE-based model for image denoising that have been contaminated by …
Implementation of the ADMM approach to constrained optimal control problem with a nonlinear time-fractional diffusion equation
In this paper, we study the inverse problem of identifying the parameters in a nonlinear
subdiffusion model from an observation defined in the given Ω1 subset of Ω. The nonlinear …
subdiffusion model from an observation defined in the given Ω1 subset of Ω. The nonlinear …
An inverse problem of identifying the coefficient in a nonlinear time-fractional diffusion equation
The paper deals with an inverse problem of identifying parameters in a nonlinear
subdiffusion model from a final observation. The nonlinear subdiffusion model involves a …
subdiffusion model from a final observation. The nonlinear subdiffusion model involves a …
A new learning space-variant anisotropic constrained-PDE for image denoising
In this paper, we propose an improved enhancement space-variant anisotropic PDE-
constrained for image denoising, based on a learning optimization procedure. Since the …
constrained for image denoising, based on a learning optimization procedure. Since the …
An optimal variable exponent model for magnetic resonance images denoising
This paper investigates a novel PDE-constrained optimization model with discontinuous
variable exponent p (x) identification. Since the parameter p is always related to a better …
variable exponent p (x) identification. Since the parameter p is always related to a better …
Fractional optimal control for deep convolutional neural networks exploring ODE-based solutions for image denoising
In recent years, Deep Convolutional Neural Networks (DCNNs) have been shown to be
effective in low-level vision tasks such as image denoising. DCNN backpropagation is …
effective in low-level vision tasks such as image denoising. DCNN backpropagation is …
An inverse problem of identifying two coefficients in a time-fractional reaction diffusion system
In this paper, we aim to study an inverse problem for determining two time-independent
coefficients in a fractional diffusion system from the final measurements. First, we prove the …
coefficients in a fractional diffusion system from the final measurements. First, we prove the …