index.rst

Optimal Image Subtraction (OIS)

OIS is a Python package and a C command-line program to perform optimal image subtraction on astronomical images.

It offers different methods to subtract images:

• Modulated multi-Gaussian kernel (as described in [alard1998])
• Delta basis kernel (as described in [bramich2008])
• Adaptive Delta Basis kernel (as described in [miller2008])

Each method can (optionally) simultaneously fit and remove common background.

Theoretical Summary

All of the methods assume we have a reference image R and a science image I that can be approximately modelled as:

I ≈ R ⊗ K + B_kg

for some background B_kg and some kernel K.

The optimal image subtraction D is then:

D = I − (R ⊗ K + B_kg)

The methods differ in their modelling of K.

Warning

In the ideal case of perfect subtraction, D should contain only noise and optical transients. In practice, tiny image misalignments, saturated stars and poor PSF fitting can leave subtraction artifacts near sources.

Contents:

installation usage cprog methods api

alard1998

"A Method for Optimal Image Subtraction" - C. Alard, R. H. Lupton, 1997.

bramich2008

"A New Algorithm For Difference Image Analysis" - D.M. Bramich, 2008.

miller2008

"Optimal Image Subtraction Method: Summary Derivations, Applications, and Publicly Shared Application Using IDL" - J. PATRICK MILLER et al., 2008.