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MATLAB ASHOKA BAIRWA
Practical – 11
Aim: Write a program remove noise from Image in MATLAB.
Theory:
Remove Noise by Linear Filtering
You can use linear filtering to remove certain types of noise. Certain filters, such as averaging or
Gaussian filters, are appropriate for this purpose. For example, an averaging filter is useful for
removing grain noise from a photograph. Because each pixel gets set to the average of the pixels in
its neighborhood, local variations caused by grain are reduced.
1. Read the image into the workspace.
MATLAB ASHOKA BAIRWA
2. Convert the image from truecolor to grayscale.
3. Add Gaussian noise to the image
MATLAB ASHOKA BAIRWA
4. Display the noisy image. Because the image is quite large, display only a portion of the
image.
5. Remove the noise using the wiener2 function
MATLAB ASHOKA BAIRWA
6. Display the processed image. Because the image is quite large, display only a portion
of the image
Before After

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Practical 111.docx

  • 1. MATLAB ASHOKA BAIRWA Practical – 11 Aim: Write a program remove noise from Image in MATLAB. Theory: Remove Noise by Linear Filtering You can use linear filtering to remove certain types of noise. Certain filters, such as averaging or Gaussian filters, are appropriate for this purpose. For example, an averaging filter is useful for removing grain noise from a photograph. Because each pixel gets set to the average of the pixels in its neighborhood, local variations caused by grain are reduced. 1. Read the image into the workspace.
  • 2. MATLAB ASHOKA BAIRWA 2. Convert the image from truecolor to grayscale. 3. Add Gaussian noise to the image
  • 3. MATLAB ASHOKA BAIRWA 4. Display the noisy image. Because the image is quite large, display only a portion of the image. 5. Remove the noise using the wiener2 function
  • 4. MATLAB ASHOKA BAIRWA 6. Display the processed image. Because the image is quite large, display only a portion of the image Before After