1 files changed, 89 insertions, 89 deletions
diff --git a/3176/CH5/EX5.4/Ex5_4.sce b/3176/CH5/EX5.4/Ex5_4.sce
index ca1fde8d4..c2aff7996 100644
--- a/3176/CH5/EX5.4/Ex5_4.sce
+++ b/3176/CH5/EX5.4/Ex5_4.sce
@@ -1,89 +1,89 @@
-//Ex5_4
-//Illustration of Adaptive Local Noise Reduction Filtering
-// Version : Scilab 5.4.1
-// Operating System : Window-xp, Window-7
-//Toolbox: Image Processing Design 8.3.1-1
-//Toolbox: SIVP 0.5.3.1-2
-//Reference book name : Digital Image Processing
-//book author: Rafael C. Gonzalez and Richard E. Woods
-
-clc;
-clear;
-close;
-xdel(winsid());
-
-///////////////// Function File /////////////////////
-function [f]=arithmetic_mean(v,m,n)
-        w=fspecial('average',m); 
-        f=imfilter(v,w); 
-endfunction
-
-function [f]=geometric_mean1(g,m,n);//gmean1() is used to filter an image using Geometric mean filter 
-    size1=m;
-    q=m*n;
-    g=double(g);
-    [nr,nc]=size(g);
-    temp=zeros(nr+2*floor(size1/2),nc+2*floor(size1/2));
-    temp(ceil(size1/2):nr+ceil(size1/2)-1,ceil(size1/2):nc+ceil(size1/2)-1)=g(1:$,1:$)
-    temp=temp+1;
-    for i=ceil(size1/2):nr+ceil(size1/2)-1
-        for j=ceil(size1/2):nc+ceil(size1/2)-1
-            t=temp(i-floor(size1/2):1:i+floor(size1/2),j-floor(size1/2):1:j+floor(size1/2)) ;
-            temp2(i,j)=prod(t);                
-        end
-    end
-    temp3=temp2.^(1/q);
-    nn=temp3(ceil(size1/2):nr+ceil(size1/2)-1,ceil(size1/2):nc+ceil(size1/2)-1)
-    f1=nn-1;
-    f=mat2gray(f1)
-endfunction
-
-
-///////////////// Main Programm /////////////////////
-A=imread("Ex5_4.tif");
-B = imnoise(A,'gaussian',0,0.01);
-[rw1 ,cl1]=size(B);
-figure;
-ShowImage(B,'Gaussian noise added'); 
-title('Image with gaussian noise','color','blue','fontsize',4);
-
-/////////////////////////////////////    Arithmetical Mean Filter    ////////////////////
-m=7;n=7;
-[f]=arithmetic_mean(B,m,n);
-figure,ShowImage(f,'Recovered Image');
-title('Restored Image with Arithmetical Mean Filter','color','blue','fontsize',4);
-
-/////////////////////////////////////    Geometric Mean Filter    ////////////////////
-m=7;n=7;
-[f]=geometric_mean1(B,m,n);
-figure,ShowImage(f,'Recovered Image');
-title('Restored Image with Geometric Mean Filter','color','blue','fontsize',4);
-
-
-
-////////////////////Adaptive Local Noise Reduction///////////////////////
-B= double(B);
-M=7;
-N=7;    
-lvar=zeros([rw1-M+1,cl1-N+1]);
-lmean=zeros([rw1-M+1,cl1-N+1]);
-temp=zeros([rw1-M+1,cl1-N+1]);
-F=zeros([rw1-M+1,cl1-N+1]);
-sz=(rw1-M+1)*(cl1-N+1);
-for i=1:rw1-M+1
-    for j=1:cl1-N+1
-        temp=B(i:i+(M-1),j:j+(N-1));
-        lmean(i,j)=mean(temp);
-        lvar(i,j)=mean(temp.*temp)-mean(temp).^2;
-     end
-end
-nvar=sum(lvar)/sz;
-lvar=max(lvar,nvar);     
-C=B(M/2:rw1-M/2,N/2:cl1-N/2);
-F=nvar./lvar;
-F=F.*(C-lmean);
-F=C-F;
-F=uint8(F);
-figure;
-ShowImage(F,'Restored');
-title('Restored Image using Adaptive Local filter','color','blue','fontsize',4);
+//Ex5_4
+//Illustration of Adaptive Local Noise Reduction Filtering
+// Version : Scilab 5.4.1
+// Operating System : Window-xp, Window-7
+//Toolbox: Image Processing Design 8.3.1-1
+//Toolbox: SIVP 0.5.3.1-2
+//Reference book name : Digital Image Processing
+//book author: Rafael C. Gonzalez and Richard E. Woods
+
+clc;
+clear;
+close;
+xdel(winsid());
+
+///////////////// Function File /////////////////////
+function [f]=arithmetic_mean(v,m,n)
+        w=fspecial('average',m); 
+        f=imfilter(v,w); 
+endfunction
+
+function [f]=geometric_mean1(g,m,n);//gmean1() is used to filter an image using Geometric mean filter 
+    size1=m;
+    q=m*n;
+    g=double(g);
+    [nr,nc]=size(g);
+    temp=zeros(nr+2*floor(size1/2),nc+2*floor(size1/2));
+    temp(ceil(size1/2):nr+ceil(size1/2)-1,ceil(size1/2):nc+ceil(size1/2)-1)=g(1:$,1:$)
+    temp=temp+1;
+    for i=ceil(size1/2):nr+ceil(size1/2)-1
+        for j=ceil(size1/2):nc+ceil(size1/2)-1
+            t=temp(i-floor(size1/2):1:i+floor(size1/2),j-floor(size1/2):1:j+floor(size1/2)) ;
+            temp2(i,j)=prod(t);                
+        end
+    end
+    temp3=temp2.^(1/q);
+    nn=temp3(ceil(size1/2):nr+ceil(size1/2)-1,ceil(size1/2):nc+ceil(size1/2)-1)
+    f1=nn-1;
+    f=mat2gray(f1)
+endfunction
+
+
+///////////////// Main Programm /////////////////////
+A=imread("Ex5_4.tif");
+B = imnoise(A,'gaussian',0,0.01);
+[rw1 ,cl1]=size(B);
+figure;
+ShowImage(B,'Gaussian noise added'); 
+title('Image with gaussian noise','color','blue','fontsize',4);
+
+/////////////////////////////////////    Arithmetical Mean Filter    ////////////////////
+m=7;n=7;
+[f]=arithmetic_mean(B,m,n);
+figure,ShowImage(f,'Recovered Image');
+title('Restored Image with Arithmetical Mean Filter','color','blue','fontsize',4);
+
+/////////////////////////////////////    Geometric Mean Filter    ////////////////////
+m=7;n=7;
+[f]=geometric_mean1(B,m,n);
+figure,ShowImage(f,'Recovered Image');
+title('Restored Image with Geometric Mean Filter','color','blue','fontsize',4);
+
+
+
+////////////////////Adaptive Local Noise Reduction///////////////////////
+B= double(B);
+M=7;
+N=7;    
+lvar=zeros([rw1-M+1,cl1-N+1]);
+lmean=zeros([rw1-M+1,cl1-N+1]);
+temp=zeros([rw1-M+1,cl1-N+1]);
+F=zeros([rw1-M+1,cl1-N+1]);
+sz=(rw1-M+1)*(cl1-N+1);
+for i=1:rw1-M+1
+    for j=1:cl1-N+1
+        temp=B(i:i+(M-1),j:j+(N-1));
+        lmean(i,j)=mean(temp);
+        lvar(i,j)=mean(temp.*temp)-mean(temp).^2;
+     end
+end
+nvar=sum(lvar)/sz;
+lvar=max(lvar,nvar);     
+C=B(M/2:rw1-M/2,N/2:cl1-N/2);
+F=nvar./lvar;
+F=F.*(C-lmean);
+F=C-F;
+F=uint8(F);
+figure;
+ShowImage(F,'Restored');
+title('Restored Image using Adaptive Local filter','color','blue','fontsize',4);
+\ No newline at end of file