Modeling and Estimation of FPN Components in CMOS Image Sensors

Fixed pattern noise (FPN) for a CCD sensor is modeled as a sample of a spatial white noise process. This model is, however, not adequate for characterizing FPN in CMOS sensors, since the readout circuitry of CMOS sensors and CCDs are very di erent. The paper presents a model for CMOS FPN as the sum of two components: a column and a pixel component. Each component is modeled by a rst order isotropic autoregressive random process, and each component is assumed to be uncorrelated with the other. The parameters of the processes characterize each component of the FPN and the correlations between neighboring pixels and neighboring columns for a batch of sensors. We show how to estimate the model parameters from a set of measurements, and report estimates for 64 64 passive pixel sensor (PPS) and active pixel sensor (APS) test structures implemented in a 0.35 micron CMOS process. High spatial correlations between pixel components were measured for the PPS structures, and between the column components in both PPS and APS. The APS pixel components were uncorrelated.