TY - JOUR
T1 - Potentials of combined visible light and near infrared imaging for driving automation
AU - Weikl, Korbinian
AU - Schroeder, Damien
AU - Stechele, Walter
N1 - Publisher Copyright:
© 2022 Society for Imaging Science and Technology. All rights reserved.
PY - 2022
Y1 - 2022
N2 - An extension of automotive imaging from the visible (VIS) to the near infrared (NIR) spectrum is promising for driving automation applications because the technology is readily available and offers potential benefits in low visibility conditions, in low light conditions with active illumination, and by collection of complementary data. We propose the evaluation of VIS-NIR imaging in simulation using an extended version of our camera simulation and optimization framework. Our extended framework generates realistic spectral irradiance data of synthetic scenes in the VIS and NIR spectral range and includes physically based camera models with characteristic increased NIR sensitivity of VIS-NIR CMOS imagers, modified automotive VIS-NIR color filter arrays and adapted image processing. We evaluate the reproduction of potential benefits of VIS-NIR imaging in our simulated camera images using exemplary night time and daylight traffic scenes, and discuss further extensions for creation of a well-balanced VIS-NIR dataset for quantitative evaluation.
AB - An extension of automotive imaging from the visible (VIS) to the near infrared (NIR) spectrum is promising for driving automation applications because the technology is readily available and offers potential benefits in low visibility conditions, in low light conditions with active illumination, and by collection of complementary data. We propose the evaluation of VIS-NIR imaging in simulation using an extended version of our camera simulation and optimization framework. Our extended framework generates realistic spectral irradiance data of synthetic scenes in the VIS and NIR spectral range and includes physically based camera models with characteristic increased NIR sensitivity of VIS-NIR CMOS imagers, modified automotive VIS-NIR color filter arrays and adapted image processing. We evaluate the reproduction of potential benefits of VIS-NIR imaging in our simulated camera images using exemplary night time and daylight traffic scenes, and discuss further extensions for creation of a well-balanced VIS-NIR dataset for quantitative evaluation.
UR - http://www.scopus.com/inward/record.url?scp=85132382820&partnerID=8YFLogxK
U2 - 10.2352/EI.2022.34.16.AVM-161
DO - 10.2352/EI.2022.34.16.AVM-161
M3 - Conference article
AN - SCOPUS:85132382820
SN - 2470-1173
VL - 34
JO - IS and T International Symposium on Electronic Imaging Science and Technology
JF - IS and T International Symposium on Electronic Imaging Science and Technology
IS - 16
M1 - 161
T2 - IS and T International Symposium on Electronic Imaging: Autonomous Vehicles and Machines, AVM 2022
Y2 - 17 January 2022 through 26 January 2022
ER -