fatmabouzidi
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j'ai essayé de programmé le filtre mais j'arrive à rien.j'ai ce code mais j'ai un problème dans la détermination des paramètres d'entrées:
Voici le code d'un filtre anisotrope:
function diff_im = anisodiff2D(im, num_iter, delta_t, kappa, option)
%ANISODIFF2D Conventional anisotropic diffusion
% DIFF_IM = ANISODIFF2D(IM, NUM_ITER, DELTA_T, KAPPA, OPTION) perfoms
% conventional anisotropic diffusion (Perona & Malik) upon a gray scale
% image. A 2D network structure of 8 neighboring nodes is considered for
% diffusion conduction.
%
% ARGUMENT DESCRIPTION:
% IM - gray scale image (MxN).
% NUM_ITER - number of iterations.
% DELTA_T - integration constant (0 <= delta_t <= 1/7).
% Usually, due to numerical stability this
% parameter is set to its maximum value.
% KAPPA - gradient modulus threshold that controls the conduction.
% OPTION - conduction coefficient functions proposed by Perona & Malik:
% 1 - c(x,y,t) = exp(-(nablaI/kappa).^2),
% privileges high-contrast edges over low-contrast ones.
% 2 - c(x,y,t) = 1./(1 + (nablaI/kappa).^2),
% privileges wide regions over smaller ones.
%
% OUTPUT DESCRIPTION:
% DIFF_IM - (diffused) image with the largest scale-space parameter.
%
% Example
% -------------
% s = phantom(512) + randn(512);
% num_iter = 15;
% delta_t = 1/7;
% kappa = 30;
% option = 2;
% ad = anisodiff2D(s,num_iter,delta_t,kappa,option);
% figure, subplot 121, imshow(s,[]), subplot 122, imshow(ad,[])
%
% See also anisodiff1D, anisodiff3D.
% References:
% 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.
%
% 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.
%
% MATLAB implementation based on Peter Kovesi's anisodiff(.):
% P. D. Kovesi. MATLAB and Octave Functions for Computer Vision and Image Processing.
% School of Computer Science & Software Engineering,
% The University of Western Australia. Available from:
% <http://www.csse.uwa.edu.au/~pk/research/matlabfns/>.
%
% Credits:
% Daniel Simoes Lopes
% ICIST
% Instituto Superior Tecnico - Universidade Tecnica de Lisboa
% danlopes (at) civil ist utl pt
% http://www.civil.ist.utl.pt/~danlopes
%
% May 2007 original version.
% Convert input image to double.
im = double(im);
% PDE (partial differential equation) initial condition.
diff_im = im;
% Center pixel distances.
dx = 1;
dy = 1;
dd = sqrt(2);
% 2D convolution masks - finite differences.
hN = [0 1 0; 0 -1 0; 0 0 0];
hS = [0 0 0; 0 -1 0; 0 1 0];
hE = [0 0 0; 0 -1 1; 0 0 0];
hW = [0 0 0; 1 -1 0; 0 0 0];
hNE = [0 0 1; 0 -1 0; 0 0 0];
hSE = [0 0 0; 0 -1 0; 0 0 1];
hSW = [0 0 0; 0 -1 0; 1 0 0];
hNW = [1 0 0; 0 -1 0; 0 0 0];
% Anisotropic diffusion.
for t = 1:num_iter
% Finite differences. [imfilter(.,.,'conv') can be replaced by conv2(.,.,'same')]
nablaN = imfilter(diff_im,hN,'conv');
nablaS = imfilter(diff_im,hS,'conv');
nablaW = imfilter(diff_im,hW,'conv');
nablaE = imfilter(diff_im,hE,'conv');
nablaNE = imfilter(diff_im,hNE,'conv');
nablaSE = imfilter(diff_im,hSE,'conv');
nablaSW = imfilter(diff_im,hSW,'conv');
nablaNW = imfilter(diff_im,hNW,'conv');
% Diffusion function.
if option == 1
cN = exp(-(nablaN/kappa).^2);
cS = exp(-(nablaS/kappa).^2);
cW = exp(-(nablaW/kappa).^2);
cE = exp(-(nablaE/kappa).^2);
cNE = exp(-(nablaNE/kappa).^2);
cSE = exp(-(nablaSE/kappa).^2);
cSW = exp(-(nablaSW/kappa).^2);
cNW = exp(-(nablaNW/kappa).^2);
elseif option == 2
cN = 1./(1 + (nablaN/kappa).^2);
cS = 1./(1 + (nablaS/kappa).^2);
cW = 1./(1 + (nablaW/kappa).^2);
cE = 1./(1 + (nablaE/kappa).^2);
cNE = 1./(1 + (nablaNE/kappa).^2);
cSE = 1./(1 + (nablaSE/kappa).^2);
cSW = 1./(1 + (nablaSW/kappa).^2);
cNW = 1./(1 + (nablaNW/kappa).^2);
end
% Discrete PDE solution.
diff_im = diff_im + ...
delta_t*(...
(1/(dy^2))*cN.*nablaN + (1/(dy^2))*cS.*nablaS + ...
(1/(dx^2))*cW.*nablaW + (1/(dx^2))*cE.*nablaE + ...
(1/(dd^2))*cNE.*nablaNE + (1/(dd^2))*cSE.*nablaSE + ...
(1/(dd^2))*cSW.*nablaSW + (1/(dd^2))*cNW.*nablaNW );
% Iteration warning.
fprintf('\rIteration %d\n',t);
end
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