图形图像处理

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Matlab

SEM2.m：源码内容

							clear all;
I=imread('SEM.bmp'); 
I=rgb2gray(I);
%if isa(I,'double')~=1 
%I=double(I);
%end
%figure;
%imshow(I);
[height width ]=size(I);
J=zeros(height,width);
%u=4;
v=2;
for u=0:7   %orientations 0-7
   
sigma = pi/3;%pi*sqrt(2^(-v/2-1));%pi*2;
sigma_2 = sigma^2;
kv = pi*2^(-v/2-1);
phiu = u*pi/8;
sigma_rule = 3*sigma/kv;    %3 sigma rule
kjx = kv*cos(phiu);
kjy = kv*sin(phiu);
for x = -sigma_rule:sigma_rule
    for y = -sigma_rule:sigma_rule
        gaussian_kernal = kv^2/sigma_2*exp(-kv^2*(x^2+y^2)/(2*sigma_2)); %gaussian kernal function
        
        if (abs(x)<=sigma_rule & abs(y)<=sigma_rule)
            gabor_real(x+sigma_rule+1,y+sigma_rule+1) = gaussian_kernal * (cos(kjx*x+kjy*y)-exp(-sigma_2/2));
            gabor_imag(x+sigma_rule+1,y+sigma_rule+1) = gaussian_kernal * sin(kjx*x+kjy*y);
        else
            gabor_real(x+sigma_rule+1,y+sigma_rule+1) = 0;
            gabor_imag(x+sigma_rule+1,y+sigma_rule+1) = 0;
        end
    end
end
Imgabout1 = conv2(I,double(gabor_imag),'same');
Regabout1 = conv2(I,double(gabor_real),'same');
gabout1 = Regabout1;
%gabout1 = Imgabout1;
%for i=2:height-1
    %for j=2:width-1
        %J(i,j)=J(i,j)+gabout1(i,j);
        %end
        %end
        J=J+gabout1;
    end
%k=255/[max(max(J))-min(min(J))]; 
%G=[J-min(min(J))]/k;
J=J/8;
for i=1:height
    for j=1:width
        if (J(i,j)<-6.5)
            J(i,j)=0;
        else J(i,j)=1;
        end
    end
end
G=[J-min(min(J))]*255/[max(max(J))-min(min(J))];
G=uint8(G);
figure,imshow(G);
    

						