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F4: Good, John
John Good (Caltech/IPAC-NExScI)
G. Bruce Berriman (Caltech/IPAC-NExScI)





Time: Tue 15.30 - 16.00
Theme: Astrophysical Data Visualization from Line Plots to Augmented and Virtual Reality
Title: Image Processing in Python With Montage

The Montage image mosaic engine (http://montage.ipac.caltech.edu; https://github.com/Caltech-IPAC/Montage) has found wide applicability in astronomy research, integration into processing environments, and is an examplar application for the development of advanced cyber-infrastructure. It is written in C to provide performance and portability. Linking C/C++ libraries to the Python kernel at run time as binary extensions allows them to run under Python at compiled speeds and enables users to take advantage of all the functionality in Python. We have built Python binary extensions of the 59 ANSI-C modules that make up version 5 of the Montage toolkit. This has involved a turning the code into a C library, with driver code fully separated to reproduce the calling sequence of the command-line tools; and then adding Python and C linkage code with the Cython library, which acts as a bridge between general C libraries and the Python interface. We will demonstrate how to use these Python binary extensions to perform image processing, including reprojecting and resampling images, rectifying background emission to a common level, creation of image mosaics that preserve the calibration and astrometric fidelity of the input images, creating visualizations with an adaptive stretch algorithm, processing HEALPix images, and analyzing and managing image metadata. The material presented here will be made freely available as a set of Jupyter notebooks posted on the Montage GitHub page. Montage is funded by the U. S. National Science Foundation (NSF) under Grant Number ACI-1642453.

Link to PDF (may not be available yet): F4.pdf