An optimized algorithm for multi-scale wideband deconvolution of radio astronomical images
arXiv:1706.06786 · doi:10.1093/mnras/stx1547
Abstract
We describe a new multi-scale deconvolution algorithm that can also be used in multi-frequency mode. The algorithm only affects the minor clean loop. In single-frequency mode, the minor loop of our improved multi-scale algorithm is over an order of magnitude faster than the CASA multi-scale algorithm, and produces results of similar quality. For multi-frequency deconvolution, a technique named joined-channel cleaning is used. In this mode, the minor loop of our algorithm is 2-3 orders of magnitude faster than CASA MSMFS. We extend the multi-scale mode with automated scale-dependent masking, which allows structures to be cleaned below the noise. We describe a new scale-bias function for use in multi-scale cleaning. We test a second deconvolution method that is a variant of the MORESANE deconvolution technique, and uses a convex optimisation technique with isotropic undecimated wavelets as dictionary. On simple, well calibrated data the convex optimisation algorithm produces visually more representative models. On complex or imperfect data, the convex optimisation algorithm has stability issues.
Accepted for publication in MNRAS
References in corpus (7)
- WSClean: an implementation of a fast, generic wide-field imager for radio astronomy
- Multi-Scale CLEAN deconvolution of radio synthesis images
- Compressed sensing imaging techniques for radio interferometry
- Correcting direction-dependent gains in the deconvolution of radio interferometric images
- The Lockman Hole project: LOFAR observations and spectral index properties of low-frequency radio sources
- Multi-Scale CLEAN: A comparison of its performance against classical CLEAN in galaxies using THINGS
- MORESANE: MOdel REconstruction by Synthesis-ANalysis Estimators. A sparse deconvolution algorithm for radio interferometric imaging