Image processing with Python and SciPy

Given that NumPy provides multidimensional arrays, and that there is core support through the Python Imaging Library to display images and manipulate images in the Python environment, it's easy to take the next step and combine these for scientific image processing. As part of our short course on Python for Physics and Astronomy we begin by exploring how Python handle image input and output

Python Imaging Library - PIL

Before we get into the broad area, there is a caveat for users of Python 3. The essential Python Imaging Library (PIL) is not yet completely compatible with new version of Python. Consequently the FITS tools we will need for astronomical image processing are also currently only supported in the mature versions of Python 2. The comments that follow are based on Python 2.7.

PIL provides functions to manipulate images, including reading, modifying and saving in various standard image formats. Its functions are documented in an on-line manual and in this handy pdf guide.

Astronomical FITS files with PyFITS

PyFITS is available from the Space Telescope Science Institute, and can be added easily to a Python installation that already and NumPy and SciPy. As of January 2013, the current version 3.1.1 of PyFITS supports all the functions needed to manage image and table data in the standard Flexibile Image Transport System (FITS) files of astronomy.