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DOE OSTI · 22679727

A Compressed Sensing-based Image Reconstruction Algorithm for Solar Flare X-Ray Observations

Felix, Simon·Bolzern, Roman·Battaglia, Marina
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Abstract

One way of imaging X-ray emission from solar flares is to measure Fourier components of the spatial X-ray source distribution. We present a new compressed sensing-based algorithm named VIS-CS, which reconstructs the spatial distribution from such Fourier components. We demonstrate the application of the algorithm on synthetic and observed solar flare X-ray data from the Reuven Ramaty High Energy Solar Spectroscopic Imager satellite and compare its performance with existing algorithms. VIS-CS produces competitive results with accurate photometry and morphology, without requiring any algorithm- and X-ray-source-specific parameter tuning. Its robustness and performance make this algorithm ideally suited for the generation of quicklook images or large image cubes without user intervention, such as for imaging spectroscopy analysis.

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79 ASTRONOMY AND ASTROPHYSICSALGORITHMSCOMPUTERIZED SIMULATIONDATA ANALYSISEMISSIONGAMMA RADIATIONIMAGE PROCESSINGPERFORMANCEPHOTOMETRYSATELLITESSOLAR FLARESSPATIAL DISTRIBUTIONSPECTROSCOPYSUNX RADIATIONX-RAY SOURCES

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Felix, Simon, Bolzern, Roman, Battaglia, Marina. 2017-11-01. A Compressed Sensing-based Image Reconstruction Algorithm for Solar Flare X-Ray Observations. https://doi.org/10.3847/1538-4357%2Faa8d1e

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