Scientists routinely use MATLAB or Octave for computational applications, and still C/C++ or Fortran for more for rigorous modelling. However Python is gaining popularity in scientific computing, as it has built-in scientific support through packages and toolkits such as SciPy and NumPy. Being open-source it also has a strong community support developing packages and sharing expertise. Given this, it is inevitable that Python had become one of the most popular, flexible programming languages used today and it is finding applications in science and engineering for everything from basic scripting to machine learning; and signal processing is not immune to the march of Python. This book explores the domain of image processing using Python, with the help of working examples and accompanying code.