Mixed Gaussian-impulse noise reduction from images using convolutional neural network
The removal of mixed-noise is an ill-posed problem due to high level of non-linearity in the
distribution of noise. Most commonly encountered mixed-noise is the combination of additive …
distribution of noise. Most commonly encountered mixed-noise is the combination of additive …
Restoration of images corrupted by Gaussian and uniform impulsive noise
E López-Rubio - Pattern Recognition, 2010 - Elsevier
Many approaches to image restoration are aimed at removing either Gaussian or uniform
impulsive noise. This is because both types of degradation processes are distinct in nature …
impulsive noise. This is because both types of degradation processes are distinct in nature …
Robust estimation approach for blind denoising
T Rabie - IEEE transactions on image processing, 2005 - ieeexplore.ieee.org
This work develops a new robust statistical framework for blind image denoising. Robust
statistics addresses the problem of estimation when the idealized assumptions about a …
statistics addresses the problem of estimation when the idealized assumptions about a …
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 …
Structured dictionary learning for image denoising under mixed gaussian and impulse noise
H Zhu, MK Ng - IEEE Transactions on Image Processing, 2020 - ieeexplore.ieee.org
Although image denoising as a basic task of image restoration has been widely studied in
the past decades, there are not many studies on mixed noise denoising. In this paper, we …
the past decades, there are not many studies on mixed noise denoising. In this paper, we …
Analysis and automatic parameter selection of a variational model for mixed Gaussian and salt-and-pepper noise removal
L Calatroni, K Papafitsoros - Inverse Problems, 2019 - iopscience.iop.org
We analyse a variational regularisation problem for mixed noise removal that has been
recently proposed in Calatroni et al (2017 SIAM J. Imaging Sci. 10 1196–233). The data …
recently proposed in Calatroni et al (2017 SIAM J. Imaging Sci. 10 1196–233). The data …
Applying traffic camera and deep learning-based image analysis to predict PM2. 5 concentrations
Background Air pollution has caused a significant burden in terms of mortality and mobility
worldwide. However, the current coverage of air quality monitoring networks is still limited …
worldwide. However, the current coverage of air quality monitoring networks is still limited …
An adaptive image filter based on the fuzzy transform for impulse noise reduction
T Schuster, P Sussner - Soft Computing, 2017 - Springer
Impulse noise, also known as impulsive noise, is one of the most common types of noise
occurring in digital images. The median filter and morphological filters are often used to …
occurring in digital images. The median filter and morphological filters are often used to …
Digital image steganography: An fft approach
T Rabie - … Technologies: 4th International Conference, NDT 2012 …, 2012 - Springer
This work describes a framework for image hiding that exploits spatial domain color
properties of natural images combined with spectral properties of the Fourier magnitude and …
properties of natural images combined with spectral properties of the Fourier magnitude and …
Blob reconstruction using unilateral second order Gaussian kernels with application to high-ISO long-exposure image denoising
G Wang, C Lopez-Molina… - Proceedings of the IEEE …, 2017 - openaccess.thecvf.com
Blob detection and image denoising are fundamental, and sometimes related, tasks in
computer vision. In this paper, we propose a blob reconstruction method using scale …
computer vision. In this paper, we propose a blob reconstruction method using scale …