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Deep learning-based super-resolution and de-noising for XMM-newton images
- Source :
- Monthly Notices of the Royal Astronomical Society, 517(3), 4054-4069. Oxford University Press
- Publication Year :
- 2022
- Publisher :
- Oxford University Press, 2022.
-
Abstract
- The field of artificial intelligence based image enhancement has been rapidly evolving over the last few years and is able to produce impressive results on non-astronomical images. In this work, we present the first application of Machine Learning based super-resolution (SR) and de-noising (DN) to enhance X-ray images from the European Space Agency’s XMM-Newton telescope. Using XMM-Newton images in band [0.5, 2] keV from the European Photon Imaging Camera pn detector (EPIC-pn), we develop XMM-SuperRes and XMM-DeNoise – deep learning-based models that can generate enhanced SR and DN images from real observations. The models are trained on realistic XMM-Newton simulations such that XMM-SuperRes will output images with two times smaller point-spread function and with improved noise characteristics. The XMM-DeNoise model is trained to produce images with 2.5× the input exposure time from 20 to 50 ks. When tested on real images, DN improves the image quality by 8.2 per cent, as quantified by the global peak-signal-to-noise ratio. These enhanced images allow identification of features that are otherwise hard or impossible to perceive in the original or in filtered/smoothed images with traditional methods. We demonstrate the feasibility of using our deep learning models to enhance XMM-Newton X-ray images to increase their scientific value in a way that could benefit the legacy of the XMM-Newton archive.
- Subjects :
- High Energy Astrophysical Phenomena (astro-ph.HE)
ILLUSTRISTNG SIMULATIONS
Astrophysics::High Energy Astrophysical Phenomena
FOS: Physical sciences
techniques: high angular resolution
Astronomy and Astrophysics
techniques: image processing
X-rays: general
DECONVOLUTION
CHANDRA
Space and Planetary Science
Computer Science::Computer Vision and Pattern Recognition
SIMILARITY
Astrophysics - Instrumentation and Methods for Astrophysics
Astrophysics - High Energy Astrophysical Phenomena
CLUSTERS
Instrumentation and Methods for Astrophysics (astro-ph.IM)
PHOTON IMAGING CAMERA
Subjects
Details
- Language :
- English
- ISSN :
- 00358711
- Volume :
- 517
- Issue :
- 3
- Database :
- OpenAIRE
- Journal :
- Monthly Notices of the Royal Astronomical Society
- Accession number :
- edsair.doi.dedup.....9a543969abe86b1aec9a67abe821523b