Journal
ASTRONOMY & ASTROPHYSICS
Volume 596, Issue -, Pages -Publisher
EDP SCIENCES S A
DOI: 10.1051/0004-6361/201629080
Keywords
methods: observational; techniques: image processing; telescopes; techniques: photometric
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Funding
- CNES (Centre National d'Etudes Spatiales), Euclid SGS (Science Ground Segment) within the Euclid Consortium
- Euclid Consortium
- European Space Agency
- European Union's Seventh Framework Programme (FP7) [FP7-SPACE-606847]
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Astrophysical images issued from different instruments and/or spectral bands often require to be processed together, either for fitting or comparison purposes. However each image is affected by an instrumental response, also known as point-spread function (PSF), that depends on the characteristics of the instrument as well as the wavelength and the observing strategy. Given the knowledge of the PSF in each band, a straightforward way of processing images is to homogenise them all to a target PSF using convolution kernels, so that they appear as if they had been acquired by the same instrument. We propose an algorithm that generates such PSF-matching kernels, based on Wiener filtering with a tunable regularisation parameter. This method ensures all anisotropic features in the PSFs to be taken into account. We compare our method to existing procedures using measured Herschel/PACS and SPIRE PSFs and simulated JWST/MIRI PSFs. Significant gains up to two orders of magnitude are obtained with respect to the use of kernels computed assuming Gaussian or circularised PSFs. A software to compute these kernels is available at https://github.com/aboucaud/pypher
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