Add random uniform noise (np.random.rand) to an image (random values from 0 - 50) then rescale the image (0-255). Use Gaussian blurring (i.e. low pass filter) with 4 different sigma values (sigma=0.5, 0.2, 1, 5 ) to reduce the effect of noise in the image (scipy.ndimage.gaussian_filter). NOTE: only blur within channels, not across channels (e.g. sigma=[1,1,0]). Plot the original image alongside the noisy and the four final (blurred) images (6 images total). Which blurring sigma was best? Explain how this option was chosen.