Improves the signal-to-noise ratio of images without degrading seriously edge contrast and resolution.

Anisotropic diffusion is now a well-established technique (see Perona & Malik, 1990), based on the resolution of partial differential equations which make the diffusion faster within objects or regions, and slower across edges.

User interface:
Number of iterations: chosen by the user
Diffusion parameter: depends on the amount of noise in the image.
Directions: 4 ==> 8-connexity (default value)  2 ==> 4-connexity
Shows the gradients: unclicked: No (default value); clicked: yes
Show only the result of last iteration : unclicked (default value): yes; clicked:
a stack of images is produced, one for each iteration (see the illustration below)


Original image
result_diffusion4 result_diffusion7 result_diffusion
4, 7 and 10 iterations of the anisotropic diffusion process.
The user may choose the result he/she is interested in (the best compromise in terms of signal-to-noise ratio, contrast, resolution...).

There is another plugin for anisotropic diffusion: