Vol 19, No 6 (2019) / Zhang

Open Access Open Access  Restricted Access Subscription Access

An adaptive loop gain selection for CLEAN deconvolution algorithm

Li Zhang, Long Xu, Ming Zhang, Zhong-Zu Wu

Abstract

Radio interferometry significantly improves the resolution of observed images, and the final result also relies heavily on data recovery. The Cotton-Schwab CLEAN (CS-Clean) deconvolution approach is a widely used reconstruction algorithm in the field of radio synthesis imaging. However, parameter tuning for this algorithm has always been a difficult task. Here, its performance is improved by considering some internal characteristics of the data. From a mathematical point of view, a peak signal-to-noise-based (PSNR-based) method was introduced to optimize the step length of the steepest descent method in the recovery process. We also found that the loop gain curve in the new algorithm is a good indicator of parameter tuning. Tests show that the new algorithm can effectively solve the problem of oscillation for a large fixed loop gain and provides a more robust recovery.

Keywords


methods: data analysis — techniques: image processing — techniques: interferometric

Full Text:

PDF


DOI: https://doi.org/10.1088/1674–4527/19/6/79

Refbacks

  • There are currently no refbacks.