A robust and simple method for filling in masked data in astronomical images

Fuente: arXiv
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Main Authors: van Dokkum, Pieter, Pasha, Imad
Format: Preprint
Published: 2023
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author van Dokkum, Pieter
Pasha, Imad
author_facet van Dokkum, Pieter
Pasha, Imad
contents Astronomical images often have regions with missing or unwanted information, such as bad pixels, bad columns, cosmic rays, masked objects, or residuals from imperfect model subtractions. In certain situations it can be essential, or preferable, to fill in these regions. Most existing methods use low order interpolations for this task. In this paper a method is described that uses the full information that is contained in the pixels just outside masked regions. These edge pixels are extrapolated inwards, using iterative median filtering. This leads to a smoothly varying spatial resolution within the filled-in regions, and ensures seamless transitions between masked pixels and good pixels. Gaps in continuous, narrow features can be reconstructed with high fidelity, even if they are large. The method is implemented in maskfill, an open-source MIT licensed Python package. Its performance is illustrated with several examples, and compared to several alternative interpolation schemes.
format Preprint
id arxiv_https___arxiv_org_abs_2312_03064
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle A robust and simple method for filling in masked data in astronomical images
van Dokkum, Pieter
Pasha, Imad
Instrumentation and Methods for Astrophysics
Astrophysics of Galaxies
Astronomical images often have regions with missing or unwanted information, such as bad pixels, bad columns, cosmic rays, masked objects, or residuals from imperfect model subtractions. In certain situations it can be essential, or preferable, to fill in these regions. Most existing methods use low order interpolations for this task. In this paper a method is described that uses the full information that is contained in the pixels just outside masked regions. These edge pixels are extrapolated inwards, using iterative median filtering. This leads to a smoothly varying spatial resolution within the filled-in regions, and ensures seamless transitions between masked pixels and good pixels. Gaps in continuous, narrow features can be reconstructed with high fidelity, even if they are large. The method is implemented in maskfill, an open-source MIT licensed Python package. Its performance is illustrated with several examples, and compared to several alternative interpolation schemes.
title A robust and simple method for filling in masked data in astronomical images
topic Instrumentation and Methods for Astrophysics
Astrophysics of Galaxies
url https://arxiv.org/abs/2312.03064