TY - JOUR
T1 - Simulating motion blur and exposure time and evaluating its effect on image quality
AU - Lin, Hao
AU - Deegan, Brian
AU - Horgan, Jonathan
AU - Ward, Enda
AU - Denny, Patrick
AU - Eising, Ciarán
AU - Glavin, Martin
AU - Jones, Edward
N1 - Publisher Copyright:
© 2023, Society for Imaging Science and Technology.
PY - 2023
Y1 - 2023
N2 - Capturing images under low light conditions generally results in loss of contrast and difficulty discerning objects for both human observers and machine vision systems. To address this, the gain and exposure time are often increased to brighten the image. This may lead to the images becoming heavily affected by noise or motion blur. The impact of motion blur on image quality is therefore an important consideration. We present a simulation in which the exposure time and motion blur can be simulated and the impact on image quality metrics can be measured. Traditional image quality metrics are investigated, as well as some recently-proposed alternatives. Our simulation incorporates the exposure time, motion blurring, camera setting, ambient lighting, a noise model, and optical blurring. The model allows the blurring of image quality targets and real-world images; in this paper, image quality targets are used. The variation in image quality as a function of motion and exposure time may be useful in system design, in particular, determining the sensitivity to relative motion between object and imaging system.
AB - Capturing images under low light conditions generally results in loss of contrast and difficulty discerning objects for both human observers and machine vision systems. To address this, the gain and exposure time are often increased to brighten the image. This may lead to the images becoming heavily affected by noise or motion blur. The impact of motion blur on image quality is therefore an important consideration. We present a simulation in which the exposure time and motion blur can be simulated and the impact on image quality metrics can be measured. Traditional image quality metrics are investigated, as well as some recently-proposed alternatives. Our simulation incorporates the exposure time, motion blurring, camera setting, ambient lighting, a noise model, and optical blurring. The model allows the blurring of image quality targets and real-world images; in this paper, image quality targets are used. The variation in image quality as a function of motion and exposure time may be useful in system design, in particular, determining the sensitivity to relative motion between object and imaging system.
UR - http://www.scopus.com/inward/record.url?scp=85169541297&partnerID=8YFLogxK
U2 - 10.2352/EI.2023.35.16.AVM-117
DO - 10.2352/EI.2023.35.16.AVM-117
M3 - Conference article
AN - SCOPUS:85169541297
SN - 2470-1173
VL - 35
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 - 117
T2 - IS and T International Symposium on Electronic Imaging: Autonomous Vehicles and Machines, AVM 2023
Y2 - 15 January 2023 through 19 January 2023
ER -