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Compute the best rank-l approximation to B and store it in the matrix rank1 (Use the commands given in the Example parts (a) and (b) on page 2, but applied to the matrix B, rather than A. Make sure you suppress the output). Step 3. Let's visualize rank1. To do that, first create C = zeros (size (A)); % semicolon! ; This creates an array of zeros, C, of the same dimension as the original image matrix A.
Step 4. Copy the rank-1 image into C as follows: C(:,:,1) C(:,:,2) C(:,:,3) = rank1; = rank1; = rank1; Include the code and the figure in your report.
Step 5: We are almost done, except for one hitch. MATLAB does all its scaling using values from 0 to 1 (and maps them to values between 0 and 255 for the graphics hardware). Lower-rank approximations to the actual image can have values that are slightly less than O and greater than 1. So we will truncate them to fit, as follows: C = max(0,min(1,0));
Step 6. View the resulting image: image (C), axis image % no semicolon

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Compute the best rank-l approximation to B and store it in the matrix rank1 (Use the commands given...

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