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diff --git a/125/CH6/EX6.13/Fig6_13.sce b/125/CH6/EX6.13/Fig6_13.sce
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+//Caption: Scilab code to perform wiener filtering of the corrupted image
+//Fig6.13
+//Page 339
+close;
+clc;
+x = imread('E:\DIP_JAYARAMAN\Chapter6\flower2.jpg'); //SIVP toolbox
+x=double(rgb2gray(x));
+sigma = 50;
+Gamma = 1;
+alpha = 1; // It indicates Wiener filter
+[M N]=size(x);
+h = zeros(M,N);
+for i = 1:5
+    for j = 1:5
+        h(i,j) = 1/25;
+    end
+end
+Freqa = fft2d(x);
+Freqh = fft2d(h);
+y = real(ifft2d(Freqh.*Freqa)) //image degradation 
+y = y+25*rand(M,N,"normal"); //Adding random noise with normal distribution
+Freqy = fft2d(y);
+Powy = abs(Freqy).^2/(M*N);
+sFreqh = Freqh.*(abs(Freqh)>0)+1/Gamma*(abs(Freqh)==0);
+iFreqh = 1/sFreqh;
+iFreqh = iFreqh'.*(abs(Freqh)*Gamma>1)+Gamma*abs(sFreqh)*iFreqh*(abs(sFreqh)*Gamma<=1);
+iFreqh = iFreqh/(max(max(abs(iFreqh))));
+Powy = Powy.*(Powy>sigma^2)+sigma^2*(Powy<=sigma^2);
+Freqg = iFreqh.*(Powy-sigma^2)./(Powy-(1-alpha)*sigma^2);
+ResFreqa = Freqg.*Freqy;
+Resa = real(ifft2d(ResFreqa));
+x = uint8(x);
+y = uint8(y);
+Resa = uint8(Resa);
+ShowImage(x,'Original Image')
+title('Original Image')
+figure
+ShowImage(y,'Degraded Image')
+title('Degraded Image')
+figure
+ShowImage(Resa,'Restored Image')
+title('Restored Image')
+\ No newline at end of file
diff --git a/125/CH6/EX6.13/Fig6_13_Image_Restoration.JPG b/125/CH6/EX6.13/Fig6_13_Image_Restoration.JPG
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index 000000000..45de86b33
--- /dev/null
+++ b/125/CH6/EX6.13/Fig6_13_Image_Restoration.JPG