2024/12/31 by Daniel G. Wright, Wright, Daniel, Karel Adámek +3
Computer Science · #FOS: Physical sciences #Image and Signal Denoising Methods #Instrumentation and Methods for Astrophysics (astro-ph.IM)
paper · pdf · doi:10.48550/arxiv.2501.01461
openalex publication_date 2024/12/31 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Data sizes for next generation radio telescopes, such as the Square Kilometre Array (SKA), are far above that of their predecessors. The CLEAN algorithm was originally developed by Högbom [1974], long before such data sizes were thought possible and is still the most popular tool used for deconvolution in interferometric imaging. In order to facilitate these new large data sizes and reduce computation time a distributed approach to the algorithm has been investigated. The serial nature of the CLEAN algorithm, due to its matching pursuit design, makes this challenging. Splitting the image into a number of tiles which can be individually deconvolved has been investigated, but this creates discontinuities in the deconvolved image and makes it difficult to deconvolve faint sources in the presence of a point spread function associated with bright sources in other tiles. A method of feedback between each of the tiles has been developed to deal with these problems. This new approach has been tested on a simulated dataset containing multiple point sources of known intensity. When compared to a standard Högbom deconvolution the tiled feedback version produced a reconstructed image, containing sources up to 2.1 Jy, which agreed to between -0.1 Jy and +0.04 Jy of the standard method across the whole deconvolved image at a speed up to 10.66 times faster.