Nonparametric denoising methods based on contourlet transform with sharp frequency localization: Application to low exposure time electron microscopy images
Image denoising is a very important step in cryo-transmission electron microscopy (cryo-
TEM) and the energy filtering TEM images before the 3D tomography reconstruction, as it …
TEM) and the energy filtering TEM images before the 3D tomography reconstruction, as it …
Likelihood estimation and wavelet transformation based optimization for minimization of noisy pixels
In recent times the statistical computation techniques are gaining a lot of interest for
analyzing the behavior of various mathematical distributions. This paper derives the …
analyzing the behavior of various mathematical distributions. This paper derives the …
Wavelet denoising based on the MAP estimation using the BKF prior with application to images and EEG signals
L Boubchir, B Boashash - IEEE Transactions on signal …, 2013 - ieeexplore.ieee.org
This paper presents a novel nonparametric Bayesian estimator for signal and image
denoising in the wavelet domain. This approach uses a prior model of the wavelet …
denoising in the wavelet domain. This approach uses a prior model of the wavelet …
Robust fuzzy c‐means clustering algorithm using non‐parametric Bayesian estimation in wavelet transform domain for noisy MR brain image segmentation
The major drawback of the fuzzy c‐means (FCM) algorithm is its sensitivity to noise. The
authors propose a new extended FCM algorithm based a non‐parametric Bayesian …
authors propose a new extended FCM algorithm based a non‐parametric Bayesian …
The estimation of Laplace random vectors in additive white Gaussian noise
IW Selesnick - IEEE Transactions on Signal Processing, 2008 - ieeexplore.ieee.org
This paper develops and compares the maximum a posteriori (MAP) and minimum mean-
square error (MMSE) estimators for spherically contoured multivariate Laplace random …
square error (MMSE) estimators for spherically contoured multivariate Laplace random …
Bayesian wavelet-based image denoising using the Gauss–Hermite expansion
SMM Rahman, MO Ahmad… - IEEE Transactions on …, 2008 - ieeexplore.ieee.org
The probability density functions (PDFs) of the wavelet coefficients play a key role in many
wavelet-based image processing algorithms, such as denoising. The conventional PDFs …
wavelet-based image processing algorithms, such as denoising. The conventional PDFs …
[PDF][PDF] Bi-parameter CGM model for approximation of a-stable PDF
Alpha stable distribution has no closed-form expression for the probability density function.
Presented is a very concise approximate model for symmetric a-stable (SaS) distribution …
Presented is a very concise approximate model for symmetric a-stable (SaS) distribution …
A study on image denoising in contourlet domain using the alpha-stable family of distributions
In the past decade, several image denoising techniques have been developed aiming at
recovering signals from noisy data as much as possible along with preserving the features of …
recovering signals from noisy data as much as possible along with preserving the features of …
A robust direction of arrival estimation method for coherently distributed sources in an impulsive noise environment
Y Liu, H Gao, M Chen, A Jakobsson… - IEEE Sensors …, 2023 - ieeexplore.ieee.org
In this work, a computationally efficient evolutionary algorithm is proposed for estimating the
direction of arrival (DOA) of coherently distributed (CD) sources corrupted by additive …
direction of arrival (DOA) of coherently distributed (CD) sources corrupted by additive …
An improved multimodal signal-image compression scheme with application to natural images and biomedical data
In this paper, a new multimodal compression scheme is proposed with the aim of
compressing jointly an image and a signal via a single codec. The key idea behind our …
compressing jointly an image and a signal via a single codec. The key idea behind our …