J/A+A/574/A74 D^3^PO algorithm (Selig+, 2015)
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Denoising, deconvolving, and decomposing photon observations.
Derivation of the D^3^PO algorithm.
Selig M., Ensslin T.
=2015A&A...574A..74S
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ADC_Keywords: Models
Keywords: methods: data analysis - methods: numerical - methods: statistical -
techniques: image processing - gamma-rays: general - X-rays: general
Abstract:
The analysis of astronomical images is a non-trivial task. The D^3^PO
algorithm addresses the inference problem of denoising, deconvolving,
and decomposing photon observations. The primary goal is the
simultaneous reconstruction of the diffuse and point-like photon flux
from a given photon count image. In order to discriminate between
these morphologically different signal components, a probabilistic
algorithm is derived in the language of information field theory based
on a hierarchical Bayesian parameter model. The signal inference
exploits prior information on the spatial correlation structure of the
diffuse component and the brightness distribution of the spatially
uncorrelated point-like sources. A maximum a posteriori solution and a
solution minimizing the Gibbs free energy of the inference problem
using variational Bayesian methods are discussed. Since the derivation
of the solution does not dependent on the underlying position space,
the implementation of the D^3^PO algorithm uses the NIFTy package to
ensure operationality on various spatial grids and at any resolution.
The fidelity of the algorithm is validated by the analysis of
simulated data, including a realistic high energy photon count image
showing a 32x32-arcmin^2^ observation with a spatial resolution of
0.1-arcmin. In all tests the D^3^PO algorithm successfully denoised,
deconvolved, and decomposed the data into a diffuse and a point-like
signal estimate for the respective photon flux components.
Description:
The code is published and maintained at github
https://github.com/mselig/d3po/releases
File Summary:
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FileName Lrecl Records Explanations
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ReadMe 80 . This file
d3po-1.0.0.tar 1490 3768 D^3^PO code, Version 1.0.0
readme.rst 447 85 Instructions for the code
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Acknowledgements:
Marco Selig, mselig(at)MPA-Garching.MPG.DE
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(End) Patricia Vannier [CDS] 27-Jan-2015