Linear filters like averaging and Gaussian filters can remove certain types of noise from images. An averaging filter is useful for removing grain noise by setting each pixel to the average of its neighbors, reducing local variations caused by grain. The program loads an image, converts it to grayscale, adds Gaussian noise, displays the noisy image, uses the wiener2 function to remove the noise, and displays the processed image showing the noise removal.

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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

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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

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6. Display the processed image. Because the image is quite large, display only a portion
of the image
Before After