Browsing by Author "Atwood, Shane"

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Blind technique for point spread function equalization with application to the Multi-Order Solar Extreme Ultraviolet Spectrograph
(2018-05) Atwood, Shane; Kankelborg, Charles C.
When combining remote sensing data from multiple instruments or multiple imaging channels, differences in point spread function (PSF) can lead to systematic error. If the PSFs are not well known, then it is difficult to determine which differences in the image data are meaningful for the object being observed and which are artifacts of PSF. Direct PSF measurements can be problematic. For example, in a sounding rocket payload, launch vibrations and acceleration, subsequent operations in micro gravity, and the impact on return to Earth may all affect PSFs. We have developed a blind method to equalize the PSFs of three distinct instrument channels, as found in the Multi-Order Solar Extreme Ultraviolet Spectrograph (MOSES). To validate our technique, we generate three synthetic images with three different PSFs, with some spectrally interesting features. Thence, we demonstrate the successful removal of PSF-induced artifacts is possible, with the genuine spectral features left intact. We also perform blind PSF equalizations on three copies of the same solar image, but with differing PSFs, after applying independent noise to each. The results accurately reproduce corrections performed in the absence of noise, with full knowledge of the PSFs. Finally, we apply PSF equalization to solar images obtained in the 2006 MOSES flight and demonstrate the removal of artifacts.
A PSF equalization technique for the Multi-Order Solar Extreme-ultraviolet Spectrograph (MOSES)
(2015-10) Atwood, Shane; Kankelborg, Charles
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.