Anisotropic Diffusion (Perona & Malik)

A set of filters that perform 1D, 2D and 3D conventional anisotropic diffusion (gray scale data).

Description

Anisotropic diffusion is a powerful image enhancer and restorer based on the PDE of heat transfer.

The implementation details are described in "P. Perona and J. Malik, Scale-Space and Edge Detection Using Anisotropic Diffusion, IEEE Transactions on Pattern Analysis and Machine Intelligence, 12(7):629-639, July 1990" and in "G. Grieg, O. Kubler, R. Kikinis, and F. A. Jolesz, Nonlinear Anisotropic Filtering of MRI Data, IEEE Transactions on Medical Imaging, 11(2):221-232, June 1992".

The algorithm was implemented to perform upon 1D, 2D and 3D gray-scale signals.

• Required Products: Image Processing Toolbox
• MATLAB release: MATLAB 7.0.4 (R14SP2)

[David Gavilan]

Is this really anisotropic? In file anisodiff2D.m there's an example using s = phantom(512) + randn(512); ad1 = anisodiff2D(s,15,1/7,30,2); Now try with a simple gaussian: hG = fspecial('gaussian',31,3); ad2 = imfilter(s,hG,'conv','symmetric'); Compare ad1 and ad2 and tell me if there's any difference.

[Daniel Lopes]

Anisotropic diffusion is known to:
- smooth the signal;
- preserve strong edges;
- enhance the contrast of edges.

Contrary to spatially filtering the signal with a Gaussian, anisotropic diffusion doesn't smooth across the edges.

A recommend the following procedures to clarify your doubt relatively to the anisotropic implementation:

- run the example of anisodiff1D(.) [the visual effect of anisotropic filtering is more evident when applied to a 1D signal]

- instead of using a Gaussian with a small sigma try a higher one, e.g.,
hG = fspecial('gaussian',31,9); % sigma = 9;
Who will see that even if you increase the number of diffusion iterations the edges will prevail, contrary to the smoothing provided by the Gaussian filter.

Another advice: try reading and understanding the code with greater attention before rating it. The references to the articles aren´t there for nothing you now! :P

[Bruno Carozza]

Thanks, works perferctly!

[jianfei ge]

Thanks!

[ivan scardanzan]

Anisotropic Diffusion
see also on matlabcentral :
File Id: 3710 Average rating: 4.62
Size: 142 KB # of reviews: 26
Submitted: 2003-07-10 Downloads: 6020
Subscribers: 8
Keywords: NonLinear Diffusion, Anisotropic Diffusion, Coherence-Enhancing Diffus

[albert j.]

 

[Daniel Mark]

Thank you very much for this excellent code.

[Andrew Rein]

Thanks for the code! it is very clearly written. For the 2D case in your code it is defined dx,dy and dd. What's the purpose of this? I didn't see it in the paper (have only read Perona). Also delta (lambda in the paper) suggest up to 1/4. Is it because you're using extra neighbours for the implementation?

[Daniel San Martin Pascal Filho]

Daniel meu chará, você me quebrou um galhão com essa implementação. Obrigado.

[Mohammad Ali Balafar]

Thanks for your code. it is very clear and useful.

[Solaree Shi]

Thanks for it!

[Forrester Cole]

 

[Forrester Cole]

Nice work. Though I think the examples could be a bit more helpful. For example, setting KAPPA = 0.2 or so, rather than KAPPA = 30, in the examples would show the anisotropic behavior more clearly. It took me a while to figure out that I needed to bring KAPPA way down from 30 before I saw results similar to Fig. 11 in the Perona and Malik paper.

[Joshua Groves]

Thanks for this. I translated your code and created a Python version that I will hopefully be using for image analysis.

[Nitin Kumar]

Thanks for sharing

[matlab user]

thank you !

one question is that I can't duplicate the fig 3 in
G. Grieg, O. Kubler, R. Kikinis, and F. A. Jolesz, Nonlinear Anisotropic Filtering of MRI Data, IEEE Transactions on Medical Imaging, 11(2):221-232, June 1992".

the fig 3 show iterative edge sharpening, but my simulation gives me reverse result... can anyone give me a sample code for results similar to fig 3?

thank you in advance.

[Anand Muglikar]

This is an awesome file that I used for driving out the noise in blood-slides and preserving the cell boundaries to detect malaria parasite.

[Faraz]

Many thanks, but it gives me a blur image of a mamogram instead of enchancing the contrast?
can you/anyone comment y?

[Xianming Liu]

Many thanks. That's just what I want.

[Tripp]

Very useful and powerful filter