It contains four parts： [1]MATLAB function:diffusion.m gauss.m [2]Linear diffusion Applying linear diffusion to images creating linear scale-space. MATLAB code: demo_lin.m Image: haifa1.bmp [3]Linear complex diffusion Applying linear complex diffusion creating Gaussian and Laplacian scale-spaces. MATLAB code: demo_cmplin.m [4]Nonlinear diffusions: Perona-Malik ["Anisotropic diffusion"] Catte et al. regularization of P-M Complex ramp-preserving diffusion Nonlinear edge preserving diffusions.The classical Perona-Malik process: the value of the diffusion coefficient is reduced near edges estimated by the first derivative. Best applied to step edges. A regularized version by Catte et al- the gradient estimation for controlling the process is smoothed by a Gaussian. Proved to be mathematically well-posed. Ramp preserving complex diffusion- best for ramp-type edges. Results are smoother with almost no staircasing effects. MATLAB code: demo_nldif.m Image: ct_scan.bmp

图像程序代码

............\demo_cmplin.m
............\demo_lin.m
............\demo_nldif.m
............\diffusion.m
............\gauss.m

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