Papers by Keyword: Anisotropic Diffusion

Abstract: The diffusion of the carbon vacancy (V_C) in n-type 4H-SiC has been studied using Deep Level Transient Spectroscopy (DLTS). Samples grown along two different crystallographic planes, (0001) or c-cut and (11-20) or a-cut, have been utilized. The samples were implanted with 4.0 MeV C ions to generate V_C’s and subsequently annealed at temperatures between 200 and 1500 °C. Following each annealing stage, concentration versus depth profiles of the V_C were obtained. The V_C is essentially immobile in both the c-cut and a-cut samples up to at least 1200 °C. The 1400 °C annealing stage, however, resulted in considerable migration, predominantly along the a-direction. Using half the difference in the Full Width at Half Maximum (FWHM) of the initial and diffused concentration profiles as a measure of the diffusion length, we deduced the diffusivity of the V_C at 1400 °C to be approximately (3.8±1.1)×10^-14 cm²/s along the c-axis and (4.1±1.2)×10^-13 cm²/s along the a-axis, indicating a substantial anisotropy for the V_C diffusion in 4H-SiC.

Abstract: The automatic detection of brain tissues such as White Matter (WM), Gray Matter (GM), and Cerebrospinal Fluid (CSF) from the MR images of the brain using segmentation is of immense interest for the early detection and diagnosing various brain-related diseases. MR imaging technology is one of the best and most reliable ways of studying the brain. Segmentation of MR images is a challenging task due to various artifacts such as noise, intensity inhomogeneity, partial volume effects and elemental texture of the image. This work proposes a region based, efficient and modern energy minimization process called as Anisotropic Multiplicative Intrinsic Component Optimization (AMICO) for the brain image segmentation in the presence of noise and intensity inhomogeneity to separate different tissues. This algorithm uses an efficient Anisotropic diffusion filter to decrease the noise. The denoised image gets segmented after the correction of intensity inhomogeneity by the MICO algorithm. The algorithm decomposes the MR brain image as two multiplicative intrinsic components, called as the component of the true image which represents the physical properties of the brain tissue and the component of bias field that is related to intensity inhomogeneity. By optimizing the values of these two components using an efficient energy minimization technique, correction of intensity inhomogeneity and segmentation of the tissues can be achieved simultaneously. Performance evaluation and the comparison with some existing methods have validated the remarkable performance of AMICO in terms of efficiency of segmentation of brain images in the presence of noise and intensity inhomogeneity.

Abstract: In this paper we present a compound anisotropic diffusion filter algorithm to apply edge sensitive ICOV operator in NCD model. According to the correlation coefficient of the ICOV operator, we obtain effective nonlinear denoising. The experiment have validated that our algorithm have better effect in smoothing and better ability in edge preservation.

Abstract: A novel model which is about the image denoising and enhancement is proposed in this article, the image denoising and enhancement increasingly becomes a bottleneck restricting the follow-up image of a series of processing On the basis of anisotropic diffusion model, an edge stopping function is introduced, which can make up the drawback that solely relies on detecting the gradient information to control the diffusion process .Using the edge stopping function position accurately on the edge so as to achieve the purpose of the noise reduction fully in the non-edge zone, but it inevitably will blur the edge information. Therefore, the further use of the shock filter in the edge enhancement is essential. Experiments show that the model can well remove the image noise and achieve good visual effect.

Abstract: In this paper, the iterative Retinex algorithm is improved to handle dynamic range compression problems. Based on the analysis of the McCann-Sobel algorithm, the iterative smoothing operation can be interpreted as an asymmetric diffusion. In order to characterized the sharp discontinuities in illumination, an edge-stopping function is introduced into the iterative procedure, which is inspired by anisotropic diffusion. Using the improved illumination estimator, dynamic range of images can be arbitrarily manipulated while suppressing undesirable artifacts. Experiments show that the proposed algorithms outperforms several derivatives for dynamic range compression based on the iterative Retinex.

Abstract: Preserving meaningful details such as blurred thin edges and low-contrast fine features is important in image de noising. A new method based on improved anisotropic diffusion model and wavelet transform is presented for image denoising. The proposed diffusion model incorporates both local gradient and gray-level variance to preserve edges and fine details while effectively removing noise in low-contrast surface images.

Abstract: Safety assessment of nuclear waste disposal in a deep geological repository requires understanding and quantifying radionuclide transport through the hosting geological formation. Radionuclide diffusion is the main transport mechanism in clay formations since they usually have small hydraulic conductivities. Thus, understanding diffusion and determining diffusion parameters under real conditions is crucial for the performance assessment of a deep geological repository. In this paper, a comparative analysis is performed which focus on the dimensions of the packed-off section where tracers are injected and the packer between the intervals, diffusion of neutral (HTO), anionic (I) and sorbing cationic tracers with different distribution coefficients (²²Na and ⁸⁵Sr) has been simulated considering the anisotropy effect. The results indicate that The expected anisotropy has been clearly measurable for the sake of a short injection interval, in the final geometric configuration, the length of injection interval is larger than the transport distance, so the anisotropy effect is not as clearly measurable as in the preliminary because practically no tracer breakthrough from one interval to the other is expected if diffusion anisotropy is confirmed. The tracer depletion in the final design is larger than in the preliminary design.

Abstract: The denoising principal of the anisotropic diffusion equation is studied. Adaptive filtering of image is realized by combining the improved image structural similarity algorithm and the anisotropic diffusion equation. This algorithm is applied to medical image segmentation. Experimental results show that the improved algorithm has good robustness and advantages in the application of adaptive medical image filtering and segmentation.

Abstract: The non-linear diffusion techniques were proposed for overcome the linear diffusion defaults. The linear diffusion was a homogeneous diffusivity with a constant conductivity. In this diffusion process, the noise and the edges were smoothed in the image. In order to prevent the edge from being smoothed during the denoising, the nonlinear diffusion was proposed by Pereona and Malik. In this method, noise was smoothed Simultaneously with the edges blurred. In diffusion processes, the conductivity is dependent on the image local information. We analyzed the ineffectiveness of isotropic and extended the work into the tensor-based anisotropic diffusion. It would be desirable to rotate the flux towards the orientation of interesting features. We compare the difference of isotroic linear and non-linear anisotropic diffusivity, and considere how to design non-linear anisotropic conductivity based on the different requires of the image filtering.

Abstract: Based on the exchange mechanism of metal islands growth on anisotropic metal surfaces, the growth processes of anisotropic Cu islands on the anisotropic Pd (110) surface are investigated by Monte Carlo simulations with realistic growth model and physical parameters. The anisotropic diffusion and anisotropic sticking of Cu adatoms are included in the simulation model after being considered the anisotropy of Pd (110) surface and compared to the experiments. It is found that the larger diffusion rate along the [110] channels of Pd (110) surface gives rise to a slower growth rate of Cu island in this direction, unless special effect of the anisotropic sticking is invoked. The simulation results show that the shape anisotropy of Cu islands is mainly due to the sticking anisotropy rather than the diffusion anisotropy.