Characterisation of CMOS Image Sensor Performance in Low Light Automotive Applications
Shane Gilroy, John O'Dwyer, Lucas Bortoleto

TL;DR
This paper presents a systematic method to characterize CMOS image sensor performance in low light automotive scenarios, focusing on noise impact to enhance night-time camera effectiveness in safety systems.
Contribution
It introduces a novel approach for evaluating CMOS sensor performance under electrical noise conditions, aiding improved design for low light automotive applications.
Findings
Sensor performance degrades with increased electrical noise.
The characterization method accurately measures noise effects on image quality.
Results support designing more robust automotive cameras for night-time use.
Abstract
The applications of automotive cameras in Advanced Driver-Assistance Systems (ADAS) are growing rapidly as automotive manufacturers strive to provide 360 degree protection for their customers. Vision systems must capture high quality images in both daytime and night-time scenarios in order to produce the large informational content required for software analysis in applications such as lane departure, pedestrian detection and collision detection. The challenge in producing high quality images in low light scenarios is that the signal to noise ratio is greatly reduced. This can result in noise becoming the dominant factor in a captured image thereby making these safety systems less effective at night. This paper outlines a systematic method for characterisation of state of the art image sensor performance in response to noise, so as to improve the design and performance of automotive…
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Taxonomy
TopicsCCD and CMOS Imaging Sensors · Infrared Target Detection Methodologies · Image Processing Techniques and Applications
