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Blur and Un-Blur an
Image using Matlab
WAQAR AHMAD (BATCH 15-16)
EE DEPARTMENT
UET JALOZAI
INTRODUCTION:
 Deblurring is the process of removing blurring artifacts from
images, such as blur caused by defocus aberration or motion
blur.
 The blur is typically modeled as the convolution of a (point
spread function) with a hypothetical sharp input image, where
both the sharp input image (which is to be recovered) and the
point spread function are unknown.
Objective:
 The purpose of this project is to make an
image blur using pre-define 2d filter which
approximate the linear motion of camera.
 The blurred image is then recovered by
applying wiener filter to display the original
image.
Matlab Code:
 clear
 close all
 clc
 pic= imread('messi.jpg');
 subplot(1,3,1);
 imshow (pic)
 title('orignal')
 %%
 x=25;
 y=25;
 h= fspecial('motion',x,y);
Code cont…
 blur = imfilter(pic,h);
 subplot(1,3,2);
 imshow (blur)
 title('blur')
 %%
 var=0.008;
 recover = deconvwnr(blur,h,var);
 subplot(1,3,3);
 imshow(recover)
 title('recover')
Figures:
Conclusion:
 In first section we read an image and in second step we
created psf function to create motion and convolved with
original image for blurring.
 At last we recovered the image by de-convolution with
the blurred image.

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Blur and un blur an image using matlab

  • 1. Blur and Un-Blur an Image using Matlab WAQAR AHMAD (BATCH 15-16) EE DEPARTMENT UET JALOZAI
  • 2. INTRODUCTION:  Deblurring is the process of removing blurring artifacts from images, such as blur caused by defocus aberration or motion blur.  The blur is typically modeled as the convolution of a (point spread function) with a hypothetical sharp input image, where both the sharp input image (which is to be recovered) and the point spread function are unknown.
  • 3. Objective:  The purpose of this project is to make an image blur using pre-define 2d filter which approximate the linear motion of camera.  The blurred image is then recovered by applying wiener filter to display the original image.
  • 4. Matlab Code:  clear  close all  clc  pic= imread('messi.jpg');  subplot(1,3,1);  imshow (pic)  title('orignal')  %%  x=25;  y=25;  h= fspecial('motion',x,y);
  • 5. Code cont…  blur = imfilter(pic,h);  subplot(1,3,2);  imshow (blur)  title('blur')  %%  var=0.008;  recover = deconvwnr(blur,h,var);  subplot(1,3,3);  imshow(recover)  title('recover')
  • 7. Conclusion:  In first section we read an image and in second step we created psf function to create motion and convolved with original image for blurring.  At last we recovered the image by de-convolution with the blurred image.