how to check whether the image is compressed or not after applying SVD on that image(regarding size of compressed image on disk)

Question

I=imread(\'cameraman.tif\');
figure(1),imshow(I)
I1=im2double(I);
[U,S,V]=svd(I1);
figure(2),imshow(I1)
for j=1:90
    I2=U(:,1:j)*S(1:j,1:j)*V(:,1:j)\';
end
figure(         


        

Answer 1

I think you're missing the point of SVD decomposition. the size of the reconstructed image will remain the same re the number of pixels. what SVD does is allow you to store/transmit less information... in other words, in your case, you can transmit 256^2 doubles or (256*j)+j+(256*j). for j of 90 it's 46170 (vs 65536)

Answer 2

Here is an illustrative example:

I = imread('cameraman.tif');
X = im2double(I);

%# SVD
[U S V] = svd(X);

%# variance explained by each eigenvector
variances = abs(diag(S).^2);
plot(cumsum(variances)./sum(variances), 'b.-'), ylim([0 1])
title('SVD'), xlabel('i^{th} Component'), ylabel('Variance explained')

%# iterate over number of components to keep
figure
subplot(121), imshow(X), title( sprintf('size=%d',numel(X)) )
subplot(122)
for p = 1:(size(U,2)/2-1)
    %# truncated SVD
    Up = U(:,1:p);
    Vp = V(:,1:p);
    Sp = diag(S(1:p,1:p));

    %# reconstruct/compress
    XHat = Up * diag(Sp) * Vp';                %'# approximation
    err = mean( abs(X(:)-XHat(:)) );           %# mean absolute error
    sz = (numel(Up) + numel(Vp) + numel(Sp));  %# new size

    %# show
    imshow(XHat)
    title( sprintf('p=%d, size=%d, err=%g', p, sz, err) )

    %# flush output
    drawnow
end