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+//Ex5_3
+// Illustration of Order Statistic filter
+//To impliment the Following Order Statistic Restoration filter 
+//                  (I)Median  (II)MAX  (III)MIN (IV)Mid Point (V)Alpha trimmed.
+
+// 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;
+close;
+clear;
+xdel(winsid())//to close all currently open figure(s).
+
+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
+
+function [f]=restoration_filter(v,type,m,n,Q,d)
+    if argn(2) ==2 then
+        m=7;n=7;Q=1.5;d=10; 
+    elseif argn(2)==5 then
+        Q=parameter;d=parameter; 
+    elseif argn(2)==4 then
+        Q=1.5;d=2; 
+    else  
+        disp('wrong number of inputs'); 
+    end 
+    
+    select type
+        
+    case'median'then
+        f=MedianFilter(v,[m n]);
+        
+    case'MIN'then
+       size1=m;
+       [nr,nc]=size(v);
+       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)=v(1:$,1:$);
+        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)) ;
+                y=gsort(t);
+                temp2(i-floor(size1/2),j-floor(size1/2))=min(y);
+            end
+        end
+        f=mat2gray(temp2);    
+    
+    case'MAX'then
+       size1=m;
+       [nr,nc]=size(v);
+       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)=v(1:$,1:$);
+        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)) ;
+                y=gsort(t);
+                temp2(i-floor(size1/2),j-floor(size1/2))=max(y);
+            end
+        end
+        f=mat2gray(temp2);
+        
+        case'Mid_Point'then
+       size1=m;
+       [nr,nc]=size(v);
+       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)=v(1:$,1:$);
+        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)) ;
+                y=gsort(t);
+                temp2(i-floor(size1/2),j-floor(size1/2))=0.5*(min(y)+max(y));
+            end
+        end
+        f=mat2gray(temp2);       
+    
+        else
+        disp('Unknownfiltertype.')
+    end     
+endfunction
+
+function [f]=alphatrim(g,m,n,d)//alphatrim()is used to filter an image using alpha-trimmed mean filter 
+    size1=m;
+    [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:$,1:$)
+
+    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)) 
+            y=gsort(t);
+            a=y(:)
+            b=a';
+            t1=b(1+d/2:$-d/2);
+            temp2(i-floor(size1/2),j-floor(size1/2))=mean(t1);
+        end
+    end    
+    f=mat2gray(temp2)   
+endfunction
+
+
+/////////////////////////////////////    Main Programm    ////////////////////
+
+gray=imread("Ex5_3.tif");
+//gray=rgb2gray(a);
+//gray=im2double(gray);
+figure,ShowImage(gray,'Gray Image');
+title('Original Image');
+[M,N]=size(gray);
+
+///////////////////////////////////       Median Filter    ////////////////////
+v=imnoise(gray,'salt & pepper',0.1);
+figure,ShowImage(v,'Noisy Image');
+title('Original Image with Salt & Pepper Noise');
+//Filtering the corrupted image with median filter
+h=restoration_filter(v,'median',3,3);
+figure,ShowImage(h,'Recovered Image');
+title('Recovered Image with Median Filter');
+//Filtering the corrupted image with median filter
+h1=restoration_filter(h,'median',3,3);
+figure,ShowImage(h1,'Recovered Image');
+title('Recovered Image with Median Filter');
+//Filtering the corrupted image with median filter
+h2=restoration_filter(h1,'median',3,3);
+figure,ShowImage(h2,'Recovered Image');
+title('Recovered Image with Median Filter');
+
+
+///////////////////////////////////       MAX Filter    ////////////////////
+temp(1:M,1:N)=0.5;
+r3=imnoise(temp,'salt & pepper',0.1);   // Generate salt & pepper Noise  
+gray_noise_pepper=gray;                  // Add Pepper Noise Only
+[r c]=find(r3==0);
+        for i=1:length(r)
+                gray_noise_pepper(r(i),c(i)) = 0; 
+        end
+figure,ShowImage(gray_noise_pepper,'Noisy Image');
+title('Noisy Image with Pepper Noise');
+
+//Filtering the Salt Noise corrupted image with MAX filter
+h=restoration_filter(gray_noise_pepper,'MAX',3,3);
+figure,ShowImage(h,'Recovered Image');
+title('Recovered Image with MAX Filter');
+
+
+////////////////////////////////////       MIN Filter    ////////////////////
+temp(1:M,1:N)=0.5;
+r3=imnoise(temp,'salt & pepper',0.1);   // Generate salt & pepper Noise 
+gray_noise_salt=gray;                  // Add salt Noise Only
+[r c]=find(r3==1);
+        for i=1:length(r)
+                gray_noise_salt(r(i),c(i)) = 255; 
+        end
+figure,ShowImage(gray_noise_salt,'Noisy Image');
+title('Noisy Image');
+
+//Filtering the Salt Noise corrupted image with MIN filter
+h=restoration_filter(gray_noise_salt,'MIN',3,3);
+figure,ShowImage(h,'Recovered Image');
+title('Recovered Image with MIN Filter');
+
+
+/////////////////////////////////////       Mid-Point Filter    ////////////////////
+//v=imnoise(gray,'gaussian',0,0.02);
+//figure,ShowImage(v,'Noisy Image');
+//title('Image with Gaussian Noise');
+////Filtering the Salt Noise corrupted image with Mid-Point filter
+//h=restoration_filter(v,'Mid_Point',3,3);
+//figure,ShowImage(h,'Recovered Image');
+//title('Recovered Image with Mid_Point Filter');
+
+
+/////////////////////////////////       Alpha Trimmed Filter    ////////////////////
+v=imnoise(gray,'gaussian',0,0.02);
+v=imnoise(v,'salt & pepper',0.05);
+figure,ShowImage(v,'Noisy Image');
+title('Image with Gaussian and Salt&Pepper Noise');
+m=5;n=5;d=5;
+[f]=arithmetic_mean(v,m,n);  // Filtering with Arithmetical mean
+figure,ShowImage(f,'Recovered Image');
+title('Recovered Image with Arithmetical Mean Filter');
+[f]=geometric_mean1(v,m,n);   // Filtering with Geometric mean
+figure,ShowImage(f,'Recovered Image');
+title('Recovered Image with Geometric Mean Filter');
+//Filtering the corrupted image with median filter
+h=restoration_filter(v,'median',5,5);  // Filtering with median Filtering
+figure,ShowImage(h,'Recovered Image');
+title('Recovered Image with Median Filter');
+f=alphatrim(v,m,n,d);   // Filtering with alphatrim Filtering
+figure,ShowImage(f,'Recovered Image');
+title('Recovered Image with Alpha Trimmed Filter');
+