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Proceedings Paper

A PSF equalization technique for the Multi-Order Solar Extreme-ultraviolet Spectrograph (MOSES)
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Paper Abstract

The Multi-Order Solar Extreme Ultraviolet Spectrograph (MOSES) is a rocket-borne slitless imaging spectrometer, designed to observe He II (30.4 nm) emission in the solar transition region. This instrument forms three simultaneous images at spectral orders m=−1, 0, +1 over an extended field of view (FOV). A multi-layer coating on the grating and thin film filters in front of the detectors defines the instrument passband. Each image contains a unique combination of spectral and spatial information. Our overarching goal in analyzing these data is to estimate a spectral line profile at every point in the FOV.

Each spectral order has different image geometry, and therefore different aberrations. Since the point spread function (PSF) differs between any two images, systematic errors are introduced when we use all three images together to invert for spectral line profiles. To combat this source of systematic error, we have developed a PSF equalization scheme.

Determination of the image PSFs is impractical for several reasons, including changes that may occur due to vibration during both launch and recovery operations. We have therefore developed a strategy using only the solar images obtained during flight to generate digital filters that modify each image so that they have the same effective PSF. Generation of the PSF equalization filters does not require that the PSFs themselves be known. Our approach begins with the assumption that there are only two things that cause the power spectra of our images to differ:

(1) aberrations; and

(2) the FOV average spectral line profile, which is known in principle from an abundance of historical data.

To validate our technique, we generate three synthetic images with three different PSFs. We compare PSF equalizations performed without knowledge of the PSF to corrections performed with that knowledge. Finally, we apply PSF equalization to solar images obtained in the 2006 MOSES flight and demonstrate the removal of artifacts.

Paper Details

Date Published: 15 October 2015
PDF: 8 pages
Proc. SPIE 9643, Image and Signal Processing for Remote Sensing XXI, 96431R (15 October 2015); doi: 10.1117/12.2194357
Show Author Affiliations
Shane Atwood, Montana State Univ. (United States)
Charles Kankelborg, Montana State Univ. (United States)

Published in SPIE Proceedings Vol. 9643:
Image and Signal Processing for Remote Sensing XXI
Lorenzo Bruzzone, Editor(s)

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