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mingwersen
Posts: **1**Member

in Matlab

Need major help on an assignment. ANy help would be nice. I have a image compression bonus assignment as follows

"1. Download the image.mat file from blackboard and load this into matlab. Do this by

typing "load image.mat" in the command prompt. There should now be the variable

A in your workspace. A has 3 dimensions. The rst two are the height and width

of the image, the last dimension is of length 3. This is because images have 3 color

planes.

2. View the image with the command "image(A)"

3. Turn A into a matrix of doubles with the command "double(A)".

4. Since each color plane can be considered a square matrix, we can perform an eigenvalue

decomposition to each plane. Do this with the function "eig(A)".

5. Try sorting the eigenvalues of each plane by magnitude (absolute value of the values).

Approximate each bit plane by only using the 100 most in

uential eigenvalues and

eigenvectors. Repeat this for 50, 25, 10, and 5. Reconstruct all 3 color planes with

each approximation. Name the reconstruction B.

6. There are likely to be imaginary values in B. Get rid of these with the command

"real(B)". Round the values of B into integers with "round(B)". Turn B into a matrix

of uint8's with "uint8(B)". View all the images. How good is the approximation? Plot

the mean squared error between A and B as a function of the number of eigenvalues

you keep.

7. Repeat steps 5 and 6 by using the eigenvalues of smallest magnitude."

I have been able to import the image, make it doubles, then i seperated it into 3 matrices so i could apply eig() onto it. thats where im lost.

"1. Download the image.mat file from blackboard and load this into matlab. Do this by

typing "load image.mat" in the command prompt. There should now be the variable

A in your workspace. A has 3 dimensions. The rst two are the height and width

of the image, the last dimension is of length 3. This is because images have 3 color

planes.

2. View the image with the command "image(A)"

3. Turn A into a matrix of doubles with the command "double(A)".

4. Since each color plane can be considered a square matrix, we can perform an eigenvalue

decomposition to each plane. Do this with the function "eig(A)".

5. Try sorting the eigenvalues of each plane by magnitude (absolute value of the values).

Approximate each bit plane by only using the 100 most in

uential eigenvalues and

eigenvectors. Repeat this for 50, 25, 10, and 5. Reconstruct all 3 color planes with

each approximation. Name the reconstruction B.

6. There are likely to be imaginary values in B. Get rid of these with the command

"real(B)". Round the values of B into integers with "round(B)". Turn B into a matrix

of uint8's with "uint8(B)". View all the images. How good is the approximation? Plot

the mean squared error between A and B as a function of the number of eigenvalues

you keep.

7. Repeat steps 5 and 6 by using the eigenvalues of smallest magnitude."

I have been able to import the image, make it doubles, then i seperated it into 3 matrices so i could apply eig() onto it. thats where im lost.

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