We are going to demonstrate how to do image processing using Python's libraries such as NumPy and SciPy.
In scientific computing, images are usually seen as n-dimensional arrays. They are usually two-dimensional arrays; in our examples, they are represented as a NumPy array data structure. Therefore, functions and operations performed on those structures are seen as matrix operations.
Images in this sense are not always two-dimensional. For medical or bio-sciences, images are data structures of higher dimensions such as 3D (having the z axis as depth or as the time axis) or 4D (having three spatial dimensions and a temporal one as the fourth dimension). We will not be using those in this recipe.
We can import ...