An adaptive diffusion coefficient scheme for image denoising based on anisotropic diffusion

2010 ◽  
Author(s):  
Hongmin Zhang ◽  
Yajuan Zhang
Keyword(s):  
Diffusion Coefficient ◽  
Image Denoising ◽  
Anisotropic Diffusion

Anisotropic Diffusion Model Based on a New Diffusion Coefficient and Fractional Order Differential for Image Denoising

2016 ◽  
Vol 16 (01) ◽  
pp. 1650003 ◽  
Author(s):  
Jianjun Yuan ◽  
Lipei Liu
Keyword(s):  
Diffusion Coefficient ◽  
Image Denoising ◽  
Diffusion Model ◽  
Fractional Order ◽  
Anisotropic Diffusion ◽  
Model Based ◽  
Proposed Model

This paper presents an improved anisotropic diffusion model which is based on a new diffusion coefficient and fractional order differential for image denoising. In the proposed model, the new diffusion coefficient can protect edges and fine characteristics from being over-smoothed. The fractional order differential is applied to weaken the staircasing effect, preserve fine characteristics. Additionally, the automatic set method of diffusion coefficient threshold is developed. Comparative experiments show that the proposed model succeeds in denoising and preserving fine characteristics.

Improved anisotropic diffusion ultrasound image denoising method based on logarithmic compression

2013 ◽  
Vol 32 (11) ◽  
pp. 3218-3220
Author(s):  
Jin YANG ◽  
Zhi-qin LIU ◽  
Yao-bin WANG ◽  
Xiao-ming GAO
Keyword(s):  
Image Denoising ◽  
Anisotropic Diffusion ◽  
Ultrasound Image ◽  
Denoising Method

Anisotropy in the Dicke Narrowing of Rotational Raman Lines (A New Measure of the Nonsphericity of Intermolecular Forces)

1972 ◽  
Vol 50 (8) ◽  
pp. 778-782 ◽  
Author(s):  
B. K. Gupta ◽  
S. Hess ◽  
A. D. May
Keyword(s):  
Diffusion Coefficient ◽  
Physical Interpretation ◽  
Anisotropic Diffusion ◽  
Scattered Light ◽  
Intermolecular Forces ◽  
Gaseous Hydrogen ◽  
Experimental Results ◽  
Scattering Angle ◽  
Collision Model

The diffusion coefficient characterizing the Dicke narrowing of the rotational Raman lines, in general, depends on the polarizations of the incident and scattered light and on the scattering angle. Experimental results for the anisotropic diffusion coefficient are presented for 90° scattering and vv and vh polarizations of the S0(1) line in gaseous hydrogen. The physical interpretation of the observed anisotropy is given with the help of a simple collision model.

Anisotropic diffusion of oxygen in slices of rat muscle

1984 ◽  
Vol 246 (1) ◽  
pp. R107-R113 ◽  
Author(s):  
L. D. Homer ◽  
J. B. Shelton ◽  
C. H. Dorsey ◽  
T. J. Williams
Keyword(s):  
Diffusion Coefficient ◽  
Fluorescence Quenching ◽  
Muscle Fiber ◽  
Extracellular Space ◽  
Anisotropic Diffusion ◽  
Muscle Fibers ◽  
Rat Muscle ◽  
Hamstring Muscles ◽  
Standard Deviations ◽  
Diffusion Coefficient Of Oxygen

The diffusion coefficient of oxygen (D) and the fluorescence quenching coefficient (K') of pyrenebutyric acid (PBA) were measured in sections of rat hamstring muscles. Values of D and K' at temperatures (Tc) of 20, 30, and 40 degrees C were determined and referred to the values in water. In sections cut parallel to the muscle fibers, D = DH2O (0.380 +/- 0.038), whereas in sections cut across the grain of the fibers, D = DH2O (0.985 +/- 0.039). Oxygen diffuses along the length of a muscle fiber over twice as rapidly as it diffuses in directions perpendicular to the long axis of the fiber. This suggests that fibers, myofibrils, or myofilaments offer substantial barriers to the diffusion of oxygen, whereas extracellular space and spaces around fibers or myofibrils or myofilaments offer no more resistance than water to the diffusion of oxygen. Corresponding estimates for K' were K' = K'H2O[0.14 (1 + 0.25 Tc)] and K' = K'H2O[0.21 (1 + 0.25 Tc)] for slices cut parallel to the long axis of muscle fibers and across the long axis, respectively. Standard deviations of K' were 9%.

scholarly journals Image denoising using anisotropic second and fourth order diffusions based on gradient vector convolution

2012 ◽  
Vol 9 (4) ◽  
pp. 1493-1511 ◽  
Author(s):  
Huaibin Wang ◽  
Yuanquan Wang ◽  
Wenqi Ren
Keyword(s):  
Image Denoising ◽  
Fourth Order ◽  
Numerical Stability ◽  
Anisotropic Diffusion ◽  
Computational Cost ◽  
Gradient Vector ◽  
Order Model ◽  
Robustness To Noise ◽  
Fourth Order Model ◽  
Low Computational Cost

In this paper, novel second order and fourth order diffusion models are proposed for image denoising. Both models are based on the gradient vector convolution (GVC) model. The second model is coined by incorporating the GVC model into the anisotropic diffusion model and the fourth order one is by introducing the GVC to the You-Kaveh fourth order model. Since the GVC model can be implemented in real time using the FFT and possesses high robustness to noise, both proposed models have many advantages over traditional ones, such as low computational cost, high numerical stability and remarkable denoising effect. Moreover, the proposed fourth order model is an anisotropic filter, so it can obviously improve the ability of edge and texture preserving except for further improvement of denoising. Some experiments are presented to demonstrate the effectiveness of the proposed models.

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