Automatic detection and characterization of random telegraph noise in sCMOS sensors

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, utilizing mixture of Gaussians fitting, to detect and characterize RTN-affected pixels from a series of dark frames. Identifying RTN contaminated pixels enables post-processing strategies that mitigate their impact and development of manufacturing quality metrics.