Normalising the image by subtracting the mean image (of all the image), from each image.
X = images.reshape(nImage, h*w)
Norm_image = X - mean_image
U, S, V = torch.svd(torch.from_numpy(Norm_image.astype(np.double)).cuda(), some=False)
Checked that variance is non zero.