In the previous sections, you learned how to use numpy.fft for a one and multi-dimensional ndarray, and saw the implementation details underneath the hood. Now it's time for some applications. In this section, we are going to use the Fourier transform to do some image processing. We will analyze the spectrum, and then we will interpolate the image to enlarge it to twice the size. First, let's download the exercise image from the Packt Publishing website blog post:
https://www.packtpub.com/books/content/python-data-scientists. Save the image to your local directory as scientist.png.
This is a RGB image, which means that, when we convert it to an ndarray, it will be three-dimensional. To simplify the exercise, we use the image module in matplotlib to read in the image and convert it to grayscale:
In [52]: from matplotlib import image
In [53]: img = image.imread('./scientist.png')
In [54]: gray_img = np.dot(img[:,:,:3], [.21, .72, .07])
In [55...