Optimized next-neighbor image cleaning method for Cherenkov Telescopes

TL;DR

This paper introduces an optimized image cleaning method for Cherenkov telescopes that leverages timing information to effectively reduce noise, improving the detection of low-light and peripheral shower images.

Contribution

It presents a simple, dynamic cut-based enhancement of the traditional next-neighbor cleaning method utilizing timing constraints for better noise suppression.

Findings

Significantly reduces noise in Cherenkov telescope images.

Improves detection efficiency for low-light and peripheral shower images.

Enhances overall image reconstruction quality.

Abstract

In photo-sensor cameras of Cherenkov telescopes the light images from particle showers always contain the background noise induced by photons of the night sky. An image cleaning procedure is needed to reduce the contribution of those noise photons in further analysis stages. The conventional topological next neighbor method lacks reconstruction efficiency for low light content images and image peripheries with low signal levels. We present here a simple optimization of the traditional next-neighbor image cleaning method that exploits the limited time duration of shower flashes and short time-difference between neighboring image pixels. This method reduces greatly the noise contribution by applying dynamical cuts in the parameter space formed by signal amplitude and time-difference between neighboring pixels