Anisotropic Diffusion
Anisotropic Diffusion in Toroidal geometries*
... The context of this work is the simulation and the modeling of nuclear fusion reaction as power source. The aim of magnetic confinement fusion is to develop a power plant that gains energy from the fusion of deuterium ...
22
Brain Tumor Segmentation of Noisy MRI Images using Anisotropic Diffusion Filter
... linear Anisotropic Diffusion Filter and morphological operators to segment the ...vision, anisotropic diffusion, also called Perona–Malik diffusion, is a technique aiming at reducing ...
7
Satellite Image Resolution Enhancement Using Multi Scale Decomposition and Anisotropic Diffusion
... Table-1 shows the proposed techniques provide improved results interns of MSE and PSNR as compared with other techniques. It can be clearly shows that the results of the proposed algorithm DT-DWT-EPS(Anisotropic ...
7
Reduction of Speckle Noise in SDOCT Retinal Images by Fuzzification and Anisotropic Diffusion Filtering
... reduction anisotropic diffusion filtering is ...noise. Anisotropic diffusion is an iterative process which makes use of simpler computation steps that compute each successive image in the ...
6
Analysis of an aggregation‐based algebraic two‐grid method for a rotated anisotropic diffusion problem
... © 2015 John Wiley & Sons, Ltd. This is the peer reviewed version of the following article: Chen, M. H., and Greenbaum, A. (2015) Analysis of an aggregation based algebraic ‐ ‐ two grid method for a rotated ...
26
Optimization of Gradient Threshold Parameter in Feature Preserving Anisotropic Diffusion for Image Denoising
... the diffusion effect is small), and for ||∇I||>k, the diffusion coefficient has a high amplitude and then the smoothing effect is ...the diffusion process has a low effect. The continuous ...
8
Image Denoising Using Anisotropic Diffusion Equations on Reflection and illumination Components of Image
... Perona-Malik anisotropic diffusion [2, 3], the Rudin– Osher–Fatemi total variation model [4], Yaroslavsky neighborhood filters [5], SUSAN filter [6], Wiener local empirical filter [7], the wavelet ...
10
Anisotropic Diffusion-Based Unsharp Masking for Sharpness Improvement in Digital Images
... An ADUSM filter is introduced in this paper, in that it begins with the input of the degraded image and parameter λ, which controls the sharpness amount of the output image. Next, the amended anisotropic ...
6
Adaptive Gradient Based and Anisotropic Diffusion Equation Filtering Algorithm for Microscopic Image Preprocessing
... In this paper, an adaptive gradient-based and anisotropic diffusion equation filtering was proposed to filter the noise of cell image. The algorithm was proposed to pre- process microscopic images, which ...
6
Anisotropic Diffusion based Micro-crack Inspection in Polycrystalline Solar Wafers
... This paper is organized as follows. Section 2 overviews the micro-crack properties in polycrystalline solar wafer. Section 3 overviews the conventional and proposed anisotropic diffusion model. Section 4 ...
5
Despeckling of SAR Images using Recursive Filter Based, Model Based and Anisotropic Diffusion Based Methods
... In this paper three despeckling methods namely Recursive filter based despeckling, Model based despeckling and Anisotropic diffusion for despeckling are compared. The MATLAB software has been used for the ...
12
Micro-crack detection of multicrystalline solar cells featuring an improved anisotropic diffusion filter and image segmentation technique
... on anisotropic diffusion and shape classi- fication is ...The anisotropic diffusion filtering with gray level-based diffusion coefficient proposed in this study produced excellent en- ...
17
Clustered Micro-Calcifications Extraction From Mammogram Images Using Cellular Automata Segmentation With Anisotropic Diffusion Filtering
... images. Anisotropic diffusion non-linear approach is very powerful tool for smoothing and edge ...[6]. Anisotropic diffusion has been mostly used in biomedical imaging where non-linear ...
5
Wavelet based Despeckling of Medical Ultrasound Images using Speckle Reducing Anisotropic Diffusion and Local Wiener Filtering
... Multiplicative speckle noise which is inherently present in med- ical ultrasound images degrades the important clinical informa- tions and badly affects the quality of the diagnosis. It is neces- sary to reduce the ...
7
Usefulness of an Anisotropic Diffusion Method in Cerebral CT Perfusion Study Using Multi Detector Row CT
... To reduce image noise, various filtering techniques have been devised [6]. In linear spatial filtering such as Gaussian filtering, the content of a pixel is given the value of the weighted average of its immediate ...
11
A review on performance evaluation of anisotropic diffusion filter for denoising the speckle noise in retinal images
... the anisotropic diffusion filter is proposed to remove the speckle noise from the retinal ...the anisotropic diffusion filter is best suitable for removing speckle noise present in the retinal ...
6
An Efficient Approach for Denoising Ultrasound Images using Anisotropic Diffusion and Teaching Learning Based Optimization
... of anisotropic diffusion to the characteristics of the multiplicative noise present in the ultrasound ...the diffusion function employing parallel processors as a result of the optimization of the ...
12
Image De Blurring and De Noising using Weiner Filter and Anisotropic Diffusion for Natural Images
... The proposed method represents how to de-blur and de-noise images using a wiener filter and Anisotropic Diffusion Filter. The Wiener filter minimizes the mean square error between the estimated random ...
7
Robust numerical schemes for anisotropic diffusion problems, a first step for turbulence modeling in Lagrangian hydrodynamics
... and diffusion tensors. In our case, the constraint on diffusion tensor can be too strong (we do not control coefficients of the tensor) and our polygonal cells can be both stretched and may be constituted ...
20
Condensed anisotropic diffusion for speckle reducton and enhancement in ultrasonography
... Many filters have been developed to cope up with speckle, with differences lying in the assumptions about the speckle model [1]. The methods described by Lee [2], Frost et al. [3], and Kuan et al. [4,5] are based on ...
17