Automatic detection and characterization of random telegraph noise in sCMOS sensors

TL;DR

This paper introduces a statistical method for detecting and characterizing random telegraph noise in sCMOS sensors, which is crucial for improving image quality and manufacturing processes in observational astronomy.

Contribution

The work presents a novel statistical approach to identify RTN-affected pixels in sCMOS sensors using dark frames, aiding in noise mitigation and quality assessment.

Findings

Effective detection of RTN-affected pixels

Improved image fidelity through noise characterization

Potential for enhanced sensor manufacturing quality metrics

Abstract

Scientific CMOS (sCMOS) image sensors are a modern alternative to typical CCD detectors and are rapidly gaining popularity in observational astronomy due to their large sizes, low read-out noise, high frame rates, and cheap manufacturing. However, numerous challenges remain in using them due to fundamental differences between CCD and CMOS architectures, especially concerning the pixel-dependent and non-Gaussian nature of their read-out noise. One of the main components of the latter is the random telegraph noise (RTN) caused by the charge traps introduced by the defects close to the oxide-silicon interface in sCMOS image sensors, which manifests itself as discrete jumps in a pixel's output signal, degrading the overall image fidelity. In this work, we present a statistical method to detect and characterize RTN-affected pixels using a series of dark frames. Identifying RTN contaminated pixels enables post-processing strategies that mitigate their impact and the development of manufacturing quality metrics.