This toolbox has functions to perform nonlinear diffusion on images. This kind of image filtering is particularly useful for reducing noise and to simplify images for further segmentation. Much of these functions are based on Perona and Malick's work, and also on J. Weickert's papers. The fast AOS diffusion is implemented. There is also 3D diffusion functions, color image diffusion and Coherence-Enhancing diffusion
I am trying "nldif" function, and find that there are two options for diffusion: one is "AOS" by aosiso.m and the other is "iso" by isodifstep.
For "AOS", the result is good when I choose stepSize = 2; But for "iso", I cannot get good result for any stepSize (from 0.01 to 1...).
I want to know what value of stepSize for "iso" case can get the same result as "aos". I suppose "aos" and "iso" should get the same result when choose proper stepSize. The only different should be the speed. Is it correct?
And when I try to feed back from "aos" result to "iso" stepSize ( (aosiso(y, g, 2) - y)/dy ), but I can not get a uniform stepSize value.
Can you help me to explain above case?
code for feedback:
========
% Calculate dy/dt
%if aos
% if plotflux
% yo = y;
% end
% y = aosiso(y,g,stepsize(i)); % updating
%else
% dy = isodifstep(y, g);
% y = y + stepsize(i) * dy; % updating
%end
tmp = y;
tmp1 = aosiso(y, g, 2) - tmp;
dy = isodifstep(y, g);
ios_step = tmp1 / dy;
=======
I am translating your matlab code in to IDL, I find that in the convolution step ('gsderiv.m'), the gaussian kernel is not normalized. It is done in 1D 'kernel=kernel/sum(kernel)', however, it is important that you do it like this:
kernel_grid=meshgrid(kernel_index,kernel_index)
kernel = exp(-.5*(kernel_grid./sigma).^2)
kernel=kernel/sum(kernel)
there is bug in almost all file for example
Input argument "x" is undefined.
in fileaosiso at 16
y = zeros(size(x));
Input argument "x" is undefined.
in file aosiso1 at 16
y = zeros(size(x));
i cant under stand why these are are coming as im using the higher version of matlab. R14
It is really great helpful to those who are doing PDE image process. The author is also a good gentlman . He had helped me many times about the toolbox's function.
It gave a great help in image segmentation for my further research.
28 Aug 2008
tg tg
good
30 Apr 2008
NEgar Sani
no comments
21 Mar 2008
kavita Jagadal
good
29 Jan 2008
Chris Coello
Really useful toolbox, working perfectly and intelligently coded. Thanks, a lot of time saved !!
09 Aug 2007
Zhiming Wang
Excellent work. Thank you!
16 Jul 2007
rasoul khayati
Your toolbox is good. But, let me know, how do you calculate Cm constant in nldif.m? your comment in head of this file is not sufficient. Please mail me any documentation about Cm. computation. thanks.
07 Apr 2007
jianfei ge
Good!Thank you!!!
21 Mar 2007
dileep kumar
Excellent work.it was very useful for bigginer like me.All lines are well commented.
Thanks alot
06 Sep 2006
Changhua Wu
This toolkit is good. However I found a bug in cedif.m
I tried it on two images and each time it generates a divide-by-zero warning. I belive this two line cause the trouble:
line 158:
dd = ( c2_m_c1 .* s1_m_s2 )./(alfa);
line 161:
d12 = -(c2_m_c1).*s12./(alfa);
15 Aug 2006
Viton Vitanis
Thanks for sharing!
16 Jun 2006
soheil kya
24 May 2006
Chao Wang
Thanks for sharing.
25 Apr 2006
Nat Anga
Great! Very well explained, very useful. Obtained very good results!!
05 Dec 2005
Matthias Schabel
Very nice work - almost trivial to use the code for my application.
04 Nov 2005
François Aspert
Very nice toolbox that save me a lot of time. With great demos and clear explanations.
01 Aug 2005
Francesco Brun
I may be wrong, but I think that in cedif.m at line 158 and 161 you have to divide by (alfa + eps) instead of (alfa). Anyway, you made a marvellous work. It would be great if you add Weickert's Edge Enhancing Anisotropic Diffusion too. I notice in documentation you put a reference to eedif.m but it's not included.
11 Mar 2005
Sharat Chikkerur
Just what I was looking for..Thanks!
20 Feb 2005
Ramesh Sen
That was very helpful.
01 Jul 2004
zhongchao shi
very valuable implementation of nonlinear diffusion filtering.
14 Jun 2004
Fredrick Mauser
Excellent and fast implementation of latest NL diffusion schemes. Particularly impressed with Coherence enhancing algorithm. Uses the optimal AOS technique. Very impressive work. Thank you for the contribution!
13 May 2004
Robert Schiessl
Good stuff. Implements fast, good algorithms for
nonlinear diffusion ... never saw something nearly as good!
29 Apr 2004
lin pan
good
22 Apr 2004
KISSI Adelaïde
A good toolbox.
22 Apr 2004
KISSI Adelaïde
A god toolbox.
12 Apr 2004
ali iskurt
Really wonderful,
I was trying to implement nonlinear diffusion filters based on transactions when I have seen this nonlinear diffusion filters' code , I caught the way how to do it .
07 Apr 2004
Simon Robidas
Wonderful toolbox. Great demos, useful comments. I especially like the nldif2demo. Saved me so much time!
25 Mar 2004
Michael Bach
This toolbox saved me a couple of days, probably weeks.
It is highly appreciated!
Thanks
06 Dec 2003
Amin Charaniya
Very useful toolbox. Was wondering how much more work would it be to extend it to n-dim.
04 Dec 2003
Alessandro Tomasi
An excellent tool! It really helps to gain a better understanding of the processes involved. Fast execution, clear comments, useful diagrams, and working examples (demos) provided. What more do you want?