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Optimal correction of distortion for High Angular Resolution images. Application to GeMS data

Instrumentation and Methods for Astrophysics · Submitted 25 Sep 2017

abstract compiled · 2026-09-23 · no language-model review

The authors' main claim The performance as well as the gain brought by this method are presented.

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arXiv ID1709.08567 (version 1)
Pith ID7WKFH6MM, Pith's permanent record of this paper and its review
CitationA. Bernard, B. Neichel, L.M. Mugnier, T. Fusco. "Optimal correction of distortion for High Angular Resolution images. Application to GeMS data." arXiv:1709.08567 (2017). https://pith.science/paper/7WKFH6MM
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What the abstract itself states, as probabilities: claims first 0.34 · states limitation 0.19 · human participants 0.02 · controlled comparison 0.08 · randomized assignment 0.01 · states quantitative result 0.05 · compares with prior results 0.24 · mentions code or data availability 0.02.

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Whether is ground-based or space-based, any optical instrument suffers from some amount of optical geometric distortion. Recently, the diffraction-limited image quality afforded by space-based telescopes and by Adaptive Optics (AO) corrected instruments on ground based-telescope, have increased the relative importance of the error terms induced by optical distortions. In particular, variable distortions present in Multi-Conjugated Adaptive Optics (MCAO) data are limiting the astrometry and photometry accuracy of such high resolution instruments. From there, the ability to deal with those phenomenon had become a critical issue for high-precision studies. We present in this paper an optimal method of distortion correction for high angular resolution images. Based on a prior-knowledge of the static distortion the method aims to correct the dynamical distortions specifically for each observation set and each frame. The method follows an inverse problem approach based on the work done by Gratadour et al. 2005 on image re-centering, and we aim to generalized it to any kind of distortion mode. The complete formalism of a Weighted Least Square minimization, as well as a detailed characterization of the error budget are presented. In particular we study the influence of different parameters such as the number of frames and the density of the field (sparse or crowed images), of the noise level, and of the aliasing effect. Finally, we show the first application of the method on real observations collected with the Gemini MCAO instrument, GeMS/GSAOI. The performance as well as the gain brought by this method are presented.

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What the classifier reports for each sentence. The number is the probability it gave the label.
#sentencerolethe authors' own workstates the main conclusionstrength
s0 Whether is ground-based or space-based, any optical instrument suffers from some amount of optical geometric distortion. background 1.00 0.05 0.02 asserted 0.99
s1 Recently, the diffraction-limited image quality afforded by space-based telescopes and by Adaptive Optics (AO) corrected instruments on ground based-telescope, have increased the relative importance of the error terms induced by optical distortions. background 1.00 0.07 0.02 asserted 1.00
s2 In particular, variable distortions present in Multi-Conjugated Adaptive Optics (MCAO) data are limiting the astrometry and photometry accuracy of such high resolution instruments. background 0.97 0.09 0.04 asserted 1.00
s3 From there, the ability to deal with those phenomenon had become a critical issue for high-precision studies. background 0.85 0.06 0.03 asserted 1.00
s4 We present in this paper an optimal method of distortion correction for high angular resolution images. contribution 1.00 0.91 0.21 asserted 1.00
s5 Based on a prior-knowledge of the static distortion the method aims to correct the dynamical distortions specifically for each observation set and each frame. method 0.97 0.60 0.08 asserted 0.98
s6 The method follows an inverse problem approach based on the work done by Gratadour et al. 2005 on image re-centering, and we aim to generalized it to any kind of distortion mode. method 0.94 0.52 0.05 asserted 0.96
s7 The complete formalism of a Weighted Least Square minimization, as well as a detailed characterization of the error budget are presented. method 0.85 0.90 0.05 asserted 0.99
s8 In particular we study the influence of different parameters such as the number of frames and the density of the field (sparse or crowed images), of the noise level, and of the aliasing effect. method 0.53 0.88 0.04 asserted 0.91
s9 Finally, we show the first application of the method on real observations collected with the Gemini MCAO instrument, GeMS/GSAOI. contribution 0.63 0.94 0.12 asserted 1.00
s10 The performance as well as the gain brought by this method are presented. result 0.80 0.87 0.19 asserted 0.77

What kind of paper the classifier reports this is: method or tool 1.00 · evidence from analysis of existing data 0.58.

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Every quoted sentence on this record is the authors'. Every label is from Pith's closed vocabulary, with the probability shown beside it. Every number in the measurements table is the authors', checked by code. Record as JSON

The paper
Original abstract

Whether is ground-based or space-based, any optical instrument suffers from some amount of optical geometric distortion. Recently, the diffraction-limited image quality afforded by space-based telescopes and by Adaptive Optics (AO) corrected instruments on ground based-telescope, have increased the relative importance of the error terms induced by optical distortions. In particular, variable distortions present in Multi-Conjugated Adaptive Optics (MCAO) data are limiting the astrometry and photometry accuracy of such high resolution instruments. From there, the ability to deal with those phenomenon had become a critical issue for high-precision studies. We present in this paper an optimal method of distortion correction for high angular resolution images. Based on a prior-knowledge of the static distortion the method aims to correct the dynamical distortions specifically for each observation set and each frame. The method follows an inverse problem approach based on the work done by Gratadour et al. 2005 on image re-centering, and we aim to generalized it to any kind of distortion mode. The complete formalism of a Weighted Least Square minimization, as well as a detailed characterization of the error budget are presented. In particular we study the influence of different parameters such as the number of frames and the density of the field (sparse or crowed images), of the noise level, and of the aliasing effect. Finally, we show the first application of the method on real observations collected with the Gemini MCAO instrument, GeMS/GSAOI. The performance as well as the gain brought by this method are presented.

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