Computer Methods in Applied Mechanics and Engineering - Special edition on the 20th Anniversary
Image selective smoothing and edge detection by nonlinear diffusion
SIAM Journal on Numerical Analysis
Solution of nonlinear diffusion appearing in image smoothing and edge detection
Applied Numerical Mathematics
A New Interpretation and improvement of the Nonlinear Anisotropic Diffusion for Image Enhancement
IEEE Transactions on Pattern Analysis and Machine Intelligence
Handbook of Image and Video Processing
Handbook of Image and Video Processing
Anisotropic Diffusion in Vector Field Visualization on Euclidean Domains and Surfaces
IEEE Transactions on Visualization and Computer Graphics
Multigrid anisotropic diffusion
IEEE Transactions on Image Processing
Efficient and reliable schemes for nonlinear diffusion filtering
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
Mode Decomposition Evolution Equations
Journal of Scientific Computing
Edge structure preserving image denoising using OAGSM/NC statistical model
Digital Signal Processing
Image denoising using SVM classification in nonsubsampled contourlet transform domain
Information Sciences: an International Journal
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In this paper we present a convection-diffusion equation for processing image denoising, edge preservation and compression. We compare it with a popular nonlinear diffusion model which has been widely implemented in image denoising for Gaussian white noise. Here we show that this convection-diffusion model effectively removes noise, especially for the mixture of Gaussian and salt-and-pepper noises. We propose the modified streamline diffusion method [Y. Shih, H.C. Elman, Modified streamline diffusion schemes for convection-diffusion problems, Comput. Methods Appl. Mech. Eng, 1998.] for the discretization of this convection-diffusion model to prevent internal layers because of the discontinuities while using the coarsening algorithm for the image compression. Numerical experiments have shown that our convection-diffusion model for removing both Gaussian and salt-and-pepper noises, efficiently and reliably preserves edges quite satisfactorily.