A weighted dictionary learning model for denoising images corrupted by mixed noise
This paper proposes a general weighted l 2-l 0 norms energy minimization model to remove
mixed noise such as Gaussian-Gaussian mixture, impulse noise, and Gaussian-impulse …
mixed noise such as Gaussian-Gaussian mixture, impulse noise, and Gaussian-impulse …
Variational-based mixed noise removal with CNN deep learning regularization
F Wang, H Huang, J Liu - IEEE Transactions on Image …, 2019 - ieeexplore.ieee.org
In this paper, the traditional model based variational methods and deep learning based
algorithms are naturally integrated to address mixed noise removal, specially for Gaussian …
algorithms are naturally integrated to address mixed noise removal, specially for Gaussian …
On the reduction of mixed Gaussian and impulsive noise in heavily corrupted color images
In this paper, a novel approach to the mixed Gaussian and impulsive noise reduction in
color images is proposed. The described denoising framework is based on the Non-Local …
color images is proposed. The described denoising framework is based on the Non-Local …
Deep unfolding network for efficient mixed video noise removal
Existing image and video denoising algorithms have focused on removing homogeneous
Gaussian noise. However, this assumption with noise modeling is often too simplistic for the …
Gaussian noise. However, this assumption with noise modeling is often too simplistic for the …
A block nonlocal TV method for image restoration
J Liu, X Zheng - SIAM Journal on Imaging Sciences, 2017 - SIAM
In this paper, we propose a block nonlocal total variation (TV) regularization method for
image restoration. We extend the existing nonlocal TV method in two aspects: first, some …
image restoration. We extend the existing nonlocal TV method in two aspects: first, some …
Divide-and-conquer framework for image restoration and enhancement
P Zhuang, X Ding - Engineering Applications of Artificial Intelligence, 2019 - Elsevier
We develop a novel divide-and-conquer framework for image restoration and enhancement
based on their task-driven requirements, which takes advantage of visual importance …
based on their task-driven requirements, which takes advantage of visual importance …
A fast segmentation method based on constraint optimization and its applications: Intensity inhomogeneity and texture segmentation
We propose a new constraint optimization energy and an iteration scheme for image
segmentation which is connected to edge-weighted centroidal Voronoi tessellation …
segmentation which is connected to edge-weighted centroidal Voronoi tessellation …
[HTML][HTML] A variational method for Abel inversion tomography with mixed Poisson-Laplace-Gaussian noise
K Linghai, W Suhua - Inverse Problems and Imaging, 2022 - aimsciences.org
Abel inversion tomography plays an important role in dynamic experiments, while most
known studies are started with a single Gaussian assumption. This paper proposes a mixed …
known studies are started with a single Gaussian assumption. This paper proposes a mixed …
Mixed noise removal based on a novel non-parametric Bayesian sparse outlier model
We develop a novel non-parametric Bayesian sparse outlier model for the problem of mixed
noise removal. Based on the assumptions of sparse data and isolated outliers, the proposed …
noise removal. Based on the assumptions of sparse data and isolated outliers, the proposed …
A non-divergence diffusion equation for removing impulse noise and mixed Gaussian impulse noise
K Shi, D Zhang, Z Guo, J Sun, B Wu - Neurocomputing, 2016 - Elsevier
In this paper, a non-divergence diffusion equation consisting of an impulse noise indicator λ
and a regularized Perona–Malik (RPM) diffusion operator is proposed for the removal of …
and a regularized Perona–Malik (RPM) diffusion operator is proposed for the removal of …