scholarly journals Image Reconstruction of Two-Dimensional Highly Scattering Inhomogeneous Medium Using MAP-Based Estimation

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Hong Qi ◽  
Yaobin Qiao ◽  
Shuangcheng Sun ◽  
Yuchen Yao ◽  
Liming Ruan
Keyword(s):  
Image Reconstruction ◽  
Inhomogeneous Medium ◽  
Measurement Errors ◽  
Field Model ◽  
Test Cases ◽  
Two Dimensional ◽  
Map Estimation ◽  
A Posteriori ◽  
Markov Random ◽  
Initial Distributions

A maximum a posteriori (MAP) estimation based on Bayesian framework is applied to image reconstruction of two-dimensional highly scattering inhomogeneous medium. The finite difference method (FDM) and conjugate gradient (CG) algorithm serve as the forward and inverse solving models, respectively. The generalized Gaussian Markov random field model (GGMRF) is treated as the regularization, and finally the influence of the measurement errors and initial distributions is investigated. Through the test cases, the MAP estimate algorithm is demonstrated to greatly improve the reconstruction results of the optical coefficients.

Bayesian Image Denoising Using an Anisotropic Markov Random Field Model

2011 ◽  
Vol 467-469 ◽  
pp. 2018-2023
Author(s):  
Yan Qiu Cui ◽  
Tao Zhang ◽  
Shuang Xu ◽  
Hou Jie Li
Keyword(s):  
Computational Complexity ◽  
Random Field ◽  
Image Denoising ◽  
Markov Random Field ◽  
Field Model ◽  
Wavelet Domain ◽  
Map Estimation ◽  
Denoising Method ◽  
Markov Random ◽  
Restoration Method

This paper presents a Bayesian denoising method based on an anisotropic Markov Random Field (MRF) model in wavelet domain in order to improve the image denoising performance and reduce the computational complexity. The classical single-resolution image restoration method using MRFs and the maximum a posteriori (MAP) estimation is extended to the wavelet domain. To obtain the accurate MAP estimation, a novel anisotropic MRF model is proposed under this framework. As compared to the simple isotropic MRF model, this new model can capture the intrascale dependencies of wavelet coefficients significantly better. Simulation results demonstrate our proposed method has a good denoising performance while reducing the computational complexity.

Conserved dynamics of a two-dimensional random-field model

1993 ◽  
Vol 48 (1) ◽  
pp. R25-R28 ◽  
Author(s):  
Madan Rao ◽  
Amitabha Chakrabarti
Keyword(s):  
Random Field ◽  
Field Model ◽  
Two Dimensional ◽  
Random Field Model

MAGNETIC FIELD AMPLIFICATION BY RELATIVISTIC SHOCKS IN AN INHOMOGENEOUS MEDIUM

2012 ◽  
Vol 08 ◽  
pp. 364-367
Author(s):  
YOSUKE MIZUNO ◽  
MARTIN POHL ◽  
JACEK NIEMIEC ◽  
BING ZHANG ◽  
KEN-ICHI NISHIKAWA ◽  
...  
Keyword(s):  
Magnetic Field ◽  
Inhomogeneous Medium ◽  
Magnetic Energy ◽  
Small Scale ◽  
Two Dimensional ◽  
Filamentary Structure ◽  
Field Amplification ◽  
Relativistic Shocks ◽  
Field Lines ◽  
Magnetohydrodynamic Simulations

We perform two-dimensional relativistic magnetohydrodynamic simulations of a mildly relativistic shock propagating through an inhomogeneous medium. We show that the postshock region becomes turbulent owing to preshock density inhomogeneity, and the magnetic field is strongly amplified due to the stretching and folding of field lines in the turbulent velocity field. The amplified magnetic field evolves into a filamentary structure in two-dimensional simulations. The magnetic energy spectrum is flatter than the Kolmogorov spectrum and indicates that the so-called small-scale dynamo is occurring in the postshock region. We also find that the amplitude of magnetic-field amplification depends on the direction of the mean preshock magnetic field.

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