Image formation – sampling and quantization

In this section, we'll describe two important concepts for image formation, namely, sampling and quantization, and see how we can resize an image with sampling and colors quantized with PIL and scikit-image libraries. We'll use a hands-on approach here and we'll define the concepts while seeing them in action. Ready?

Let's start by importing all of the required packages:

% matplotlib inline # for inline image display inside notebook
from PIL import Image
from skimage.io import imread, imshow, show
import scipy.fftpack as fp
from scipy import ndimage, misc, signal
from scipy.stats import signaltonoise
from skimage import data, img_as_float
from skimage.color import rgb2gray
from skimage.transform import rescale
import matplotlib.pylab as pylab
import numpy as np
import numpy.fft
import timeit

Sampling

Sampling refers to the selection/rejection of image pixels, which means that it is a spatial operation. We can use sampling to increase or reduce the...