scholarly journals OPTIMAL NONLINEAR IMAGE DENOISING METHODS IN HEAVY-TAILED NOISE ENVIRONMENTS

2007 ◽  
Keyword(s):  
Image Denoising ◽  
Heavy Tailed

LOCALLY ADAPTIVE MULTISCALE BAYESIAN METHOD FOR IMAGE DENOISING BASED ON BIVARIATE NORMAL INVERSE GAUSSIAN DISTRIBUTIONS

2008 ◽  
Vol 06 (04) ◽  
pp. 653-664 ◽  
Author(s):  
MOHAMAD FOROUZANFAR ◽  
HAMID ABRISHAMI MOGHADDAM ◽  
SONA GHADIMI
Keyword(s):  
Statistical Model ◽  
Image Denoising ◽  
Minimum Mean Square Error ◽  
Model Parameters ◽  
Inverse Gaussian ◽  
Wavelet Coefficients ◽  
Bivariate Normal ◽  
Wide Range ◽  
Heavy Tailed ◽  
Normal Inverse Gaussian

Recently, the use of wavelet transform has led to significant advances in image denoising applications. Among wavelet-based denoising approaches, the Bayesian techniques give more accurate estimates. Considering interscale dependencies, these estimates become closer to the original image. In this context, the choice of an appropriate model for wavelet coefficients is an important issue. The performance can also be improved by estimating model parameters in a local neighborhood. In this paper, we propose the bivariate normal inverse Gaussian (NIG) distribution, which can model a wide range of heavy-tailed to less heavy-tailed processes, to model the local wavelet coefficients at adjacent scales. We will show that this new statistical model is superior to the conventional generalized Gaussian (GG) model. Then, a minimum mean square error-based (MMSE-based) Bayesian estimator is designed to effectively remove noise from wavelet coefficients. Exploiting this new statistical model in the dual-tree complex wavelet domain, we achieved state-of-the-art performance among related recent denoising approaches, both visually and in terms of peak signal-to-noise ratio (PSNR).

An Alternative to Cohen's κ

2006 ◽  
Vol 11 (1) ◽  
pp. 12-24 ◽  
Author(s):  
Alexander von Eye
Keyword(s):  
Simulation Study ◽  
Null Hypothesis ◽  
Categorical Variables ◽  
Alternative Measure ◽  
Rater Agreement ◽  
Verbal Processing ◽  
Heavy Tailed ◽  
Applicant Selection

At the level of manifest categorical variables, a large number of coefficients and models for the examination of rater agreement has been proposed and used. The most popular of these is Cohen's κ. In this article, a new coefficient, κ s , is proposed as an alternative measure of rater agreement. Both κ and κ s allow researchers to determine whether agreement in groups of two or more raters is significantly beyond chance. Stouffer's z is used to test the null hypothesis that κ s = 0. The coefficient κ s allows one, in addition to evaluating rater agreement in a fashion parallel to κ, to (1) examine subsets of cells in agreement tables, (2) examine cells that indicate disagreement, (3) consider alternative chance models, (4) take covariates into account, and (5) compare independent samples. Results from a simulation study are reported, which suggest that (a) the four measures of rater agreement, Cohen's κ, Brennan and Prediger's κ n , raw agreement, and κ s are sensitive to the same data characteristics when evaluating rater agreement and (b) both the z-statistic for Cohen's κ and Stouffer's z for κ s are unimodally and symmetrically distributed, but slightly heavy-tailed. Examples use data from verbal processing and applicant selection.

A Power Thresholding Function-based Wavelet Image Denoising Method

2018 ◽  
Vol 62 (1) ◽  
pp. 105061-1050611 ◽  
Author(s):  
Zhidan Yan ◽  
Wenyi Xu ◽  
Chunmei Yang
Keyword(s):  
Image Denoising ◽  
Denoising Method ◽  
Wavelet Image ◽  
Thresholding Function

Zero-filling Technique in Fresnel Transfrom Image Reconstruction for MR Image Denoising

PIERS Online ◽  
2005 ◽  
Vol 1 (4) ◽  
pp. 473-477
Author(s):  
Bin-Rong Wu ◽  
Satoshi Ito ◽  
Yoshitsugu Kamimura ◽  
Yoshifumi Yamada
Keyword(s):  
Image Reconstruction ◽  
Image Denoising ◽  
Mr Image

An image Denoising Method Based On Multi Resulation Bilateral Filter

2018 ◽  
Vol 6 (12) ◽  
pp. 448-452
Author(s):  
Md Shaiful Islam Babu ◽  
Kh Shaikh Ahmed ◽  
Md Samrat Ali Abu Kawser ◽  
Ajkia Zaman Juthi
Keyword(s):  
Image Denoising ◽  
Bilateral Filter ◽  
Denoising Method

Image Denoising by Curvelets

2008 ◽  
Vol 4 (1) ◽  
pp. 63-68
Author(s):  
G. Jagadeeswar Reddy ◽  
◽  
T. Jaya Chandra Prasad ◽  
M. N. Giriprasad ◽  
◽  
...  
Keyword(s):  
Image Denoising
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