CMOS image sensors are used in most of the camera systems today. For achieving a high image quality it is essential to compensate for fixed pattern noise. Compensation can be carried out by subtracting an estimated noise value per pixel, either directly on the sensor or in the digital processing. Unfortunately these values are different for each camera and will vary for different exposure times, camera mode settings and temperature. This poses additional challenges for high-end moving picture camera systems. We present a new algorithm for improved fixed pattern noise compensation that extends the currently available linear models. Measurements of a real world camera system and a simulation are used to show the improvements with our algorithm. Significant improvement of the compensated fixed pattern noise over a wide exposure range is shown. This allows the operation of the camera system at a much wider range of frame rates and especially long exposures are now possible. Our algorithm can be implemented without increasing the required memory bandwidth which saves power, size and cost.
[1]
Hao Min,et al.
Modeling and estimation of FPN components in CMOS image sensors
,
1998,
Electronic Imaging.
[2]
Abbas El Gamal,et al.
Method for estimating quantum efficiency for CMOS image sensors
,
1998,
Electronic Imaging.
[3]
B. Choubey,et al.
Modelling of high dynamic range logarithmic CMOS image sensors
,
2004,
Proceedings of the 21st IEEE Instrumentation and Measurement Technology Conference (IEEE Cat. No.04CH37510).
[4]
I. McLean.
Electronic imaging in astronomy : detectors and instrumentation
,
1997
.
[5]
Abbas El Gamal,et al.
Analysis of temporal noise in CMOS APS
,
1999,
Electronic Imaging.
[6]
Joaquim Salvi,et al.
Review of CMOS image sensors
,
2006,
Microelectron. J..
[7]
A. Theuwissen,et al.
Leakage current modeling of test structures for characterization of dark current in CMOS image sensors
,
2003
.