  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 (RHESSI) 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 generation of quicklook images or large image
cubes without user intervention, such as for imaging spectroscopy analysis.
