IN PYTHON

4. For the given image do the following: a) Reconstruct the image using SVD b) Reconstruct the image using PCA Compute the reconstructed image for different top k singular values (in case of SVD) and eigenvalues (in case of PCA). For different values of k plot the reconstructed image by SVD and PCA side by side. Also calculate the Frobenius norm of the difference matrix between the reconstructed and actual image for both SVD and PCA. Title of the reconstructed plot should be the value of k and the corresponding Frobenius norm Note: Direct use of SVD and PCA functions are not allowed. You may use inbuilt functions to find the eigenvalues and eigenvectors