Fundamental Limitations of Pixel Based Image Deconvolution in Radio Astronomy

TL;DR

This paper investigates the fundamental limitations of pixel-based deconvolution methods in radio astronomy, especially for extended sources, and explores orthonormal basis functions as a potential improvement over traditional CLEAN algorithms.

Contribution

It identifies the limitations of pixelization in deconvolving extended sources and proposes using orthonormal basis functions for improved modeling.

Findings

Pixelization limits deconvolution accuracy for extended sources.

Orthonormal basis functions can outperform pixel-based methods.

Challenges remain in optimizing basis function selection.

Abstract

Deconvolution is essential for radio interferometric imaging to produce scientific quality data because of finite sampling in the Fourier plane. Most deconvolution algorithms are based on CLEAN which uses a grid of image pixels, or clean components. A critical matter in this process is the selection of pixel size for optimal results in deconvolution. As a rule of thumb, the pixel size is chosen smaller than the resolution dictated by the interferometer. For images consisting of unresolved (or point like) sources, this approach yields optimal results. However, for sources that are not point like, in particular for partially resolved sources, the selection of right pixel size is still an open issue. In this paper, we investigate the limitations of pixelization in deconvolving extended sources. In particular, we pursue the usage of orthonormal basis functions to model extended sources yielding better results than by using clean components.