Distributed multi-frequency image reconstruction for radio-interferometry

TL;DR

This paper presents an improved parallel implementation of the MUFFIN algorithm for radio-interferometric image reconstruction, enabling efficient large-scale spatio-spectral data processing with comparable performance to previous methods.

Contribution

It introduces a parallelized version of MUFFIN that utilizes IUWT wavelet transforms, facilitating large-scale, high-fidelity 3D image reconstruction in radio interferometry.

Findings

IUWT-based MUFFIN performs well at large scale

Parallel implementation improves computational efficiency

Comparable results to previous union of bases approach

Abstract

The advent of enhanced technologies in radio interferometry and the perspective of the SKA telescope bring new challenges in image reconstruction. One of these challenges is the spatio-spectral reconstruction of large (Terabytes) data cubes with high fidelity. This contribution proposes an alternative implementation of one such 3D prototype algorithm, MUFFIN (MUlti-Frequency image reconstruction For radio INterferometry), which combines spatial and spectral analysis priors. Using a recently proposed primal dual algorithm, this new version of MUFFIN allows a parallel implementation where computationally intensive steps are split by spectral channels. This parallelization allows to implement computationally demanding translation invariant wavelet transforms (IUWT), as opposed to the union of bases used previously. This alternative implementation is important as it opens the possibility of comparing these efficient dictionaries, and others, in spatio-spectral reconstruction. Numerical results show that the IUWT-based version can be successfully implemented at large scale with performances comparable to union of bases.