On the efficiency of techniques for the reduction of impulsive noise in astronomical images

TL;DR

This paper reviews and compares various impulsive noise filtering techniques for astronomical images, evaluating their effectiveness across different imaging conditions and noise characteristics to guide optimal image processing.

Contribution

It provides a comprehensive comparison of impulsive noise filtering methods using synthetic and real astronomical images, highlighting their suitability for different scenarios.

Findings

Certain filtering methods outperform others depending on noise distribution.

Filtering effectiveness varies with stellar profile width and signal-to-noise ratio.

The study offers guidelines for selecting optimal noise reduction techniques in astronomical imaging.

Abstract

The impulsive noise in astronomical images originates from various sources. It develops as a result of thermal generation in pixels, collision of cosmic rays with image sensor or may be induced by high readout voltage in Electron Multiplying CCD (EMCCD). It is usually efficiently removed by employing the dark frames or by averaging several exposures. Unfortunately, there are some circumstances, when either the observed objects or positions of impulsive pixels evolve and therefore each obtained image has to be filtered independently. In this article we present an overview of impulsive noise filtering methods and compare their efficiency for the purpose of astronomical image enhancement. The employed set of noise templates consists of dark frames obtained from CCD and EMCCD cameras working on ground and in space. The experiments conducted on synthetic and real images, allowed for drawing numerous conclusions about the usefulness of several filtering methods for various: (1) widths of stellar profiles, (2) signal to noise ratios, (3) noise distributions and (4) applied imaging techniques. The results of presented evaluation are especially valuable for selection of the most efficient filtering schema in astronomical image processing pipelines.