1. Design a 220×220 black image with a 30×30 centered white square and then find its Fourier Transform 2. Rotate the square in image 30 and find its Fourier Transform 3. Translate the rectangle in image to another location and find its Fourier Transform 4. Scale the rectangle in image into 40x40 and find its Fourier Transform 5. Display all the images above as in video using subplot Task 2: Write a Matlab code to read 'eight.tif' image and to do the following: a. Add 'gaussian' noise into the image with 0 mean and 0.005 variance and save it in a noisy_img. b. Apply a 5 x 5 average filter with replicate border into the noisy img, and display the result. C. Apply a Gaussian low-pass filter on the noisy img with D0=42 and D0=25 and display the results
1. Design a 220×220 black image with a 30×30 centered white square and then find its Fourier Transform 2. Rotate the square in image 30 and find its Fourier Transform 3. Translate the rectangle in image to another location and find its Fourier Transform 4. Scale the rectangle in image into 40x40 and find its Fourier Transform 5. Display all the images above as in video using subplot Task 2: Write a Matlab code to read 'eight.tif' image and to do the following: a. Add 'gaussian' noise into the image with 0 mean and 0.005 variance and save it in a noisy_img. b. Apply a 5 x 5 average filter with replicate border into the noisy img, and display the result. C. Apply a Gaussian low-pass filter on the noisy img with D0=42 and D0=25 and display the results
Chapter7: Input/output Technology
Section: Chapter Questions
Problem 1VE
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Matlab

Transcribed Image Text:1. Design a 220×220 black image with a 30×30 centered white square and then
find its Fourier Transform
2. Rotate the square in image 30 and find its Fourier Transform
3. Translate the rectangle in image to another location and find its Fourier
Transform
4. Scale the rectangle in image into 40×40 and find its Fourier Transform
5. Display all the images above as in video using subplot
Task 2:
Write a Matlab code to read 'eight.tif' image and to do the following:
a. Add 'gaussian' noise into the image with 0 mean and 0.005 variance and
save it in a noisy img.
b. Apply a 5 x 5 average filter with replicate border into the noisy img, and
display the result.
Apply a Gaussian low-pass filter on the noisy img with D0=42 and D0=25
and display the results
C.
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