Reconstructing Images from Projections Using the Maximum-Entropy Method. Numerical Simulations of Low-Aspect Astrotomography

TL;DR

This paper demonstrates that the maximum-entropy method (MEM) improves image reconstruction quality from limited projections in low-aspect astrotomography, especially for sources with extended features, and introduces a difference-mapping technique for complex structures.

Contribution

It introduces a generalized MEM with difference-mapping for sign-variable functions, enhancing image reconstruction of complex sources in low-aspect astrotomography.

Findings

MEM outperforms Hogbom CLEAN for extended sources

Difference-mapping improves reconstruction of mixed-structure sources

Numerical simulations validate the effectiveness of the proposed methods

Abstract

The reconstruction of images from a small number of projections using the maximum-entropy method (MEM) with the Shannon entropy is considered. MEM provides higher-quality image reconstruction for sources with extended components than the Hogbom CLEAN method, which is also used in low-aspect astrotomography. The quality of image reconstruction for sources with mixed structure containing bright, compact features embedded in a comparatively weak, extended base can be further improved using a difference-mapping method, which requires a generalization of MEM for the reconstruction of sign-variable functions.We draw conclusions based on the results of numerical simulations for a number of model radio sources with various morphologies.