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Please see the attached file for details.. Report is required. The work should be solely yours and not plagerized from any source. No use of AI.
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ECE 5256
Chap 6 Improved filters
In this project, you will read in an image, add noise to it, attempt to remove the noise with
three different filters, and then compare the results.
Use an image that has values from about 0-255. Make sure you convert the images to precision
“double” before adding noise.
Add noise to the image with the randn command. Use a standard deviation of 10.
For example: NoisyImage = Image + 10*randn(size(Image)); should work.
1 Filter the image with one of the filters from slides 17, 18, 19 of slideset 12 (don’t use the
arithmetic mean filter). Adjust the parameters of the filter until you get the best MSE that you
can. The MSE is a scaler and is calculated as: ((RestoredImage – Images).^2)/(number of
pixels in an image). Although the number may be small, dividing by the number pixels allows
comparison between different size images and different images.
2 Repeat the above process using an order statistic filter from slide 23, and determine the best
parameter for the filter you have chosen.
3 Also use the adaptive filter on slide 28 to filter the noise and adjust the parameters until you
get the lowest MSE.
Turn in:
1 Brief description of what you did.
2 The three filters, the parameters for the best results, and the MSE value.
3 Program listing.
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