VIS CS ALGORITHM
VIS_CS - Compressed Sensing image reconstruction algorithm based on visibilities
VIS CS is a Compressed Sensing-based algorithm that reconstructs the X-ray source distribution from the Fourier components measured by RHESSI.
The VIS_CS algorithm uses a custom Gaussian basis on the assumption that sources can be represented as linear combinations of a number of Gaussian distributions. This Gaussian basis is an overcomplete basis consisting of two-dimensional Gaussian distributions of various sizes, orientations, and locations in the xy-plane. VIS_CS randomly samples up to 10^6 basis functions from the infinite set of Gaussian distributions.
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 well-suited for generation of quicklook images or large image cubes without user intervention, such as for imaging spectroscopy analysis.
Using the VIS_CS algorithm at the command line:
| Select algorithm | o->set, image_algorithm='vis_cs' | or 'vcs' or 'vis_cs' or 'hsi_vis_cs' |
|---|---|---|
| Object Class | HSI_VIS_CS | |
| Extract Object | cs_obj = o->get(/obj,class='hsi_vis_cs') | Extract the object used in the hsi_image object, o |
| Parameter Prefix | vis_sc, e.g. | All parameter names specific to this algorithm have this prefix |
| Parameter Table | VIS_CS Object Parameter Table | List and short description of control and info parameters specific to this algorithm |
Links:
- A Compressed Sensing-based Image Reconstruction Algorithm for Solar Flare X-Ray Observations - Felix, Bolzern, Battaglia (2017)
