This paper evaluates the operation of self-correcting active pixel sensors presented in  using both Signal-to-Noise Ratio and Dynamic Range figures. The evaluation is based on a simplified Active Pixel Sensing (APS) model. We show that in the absence of stuck faults (i.e., no errors) the performance of the system suffers from considerable degradation especially at low illumination (i.e., typical indoor scenes). We use the same model to quantify the number of defective pixels under which self correction is beneficial and evaluate the quality of the resultant image
Proc. SPIE. 4966, Microarrays and Combinatorial Technologies for Biomedical Applications: Design, Fabrication, and Analysis
KEYWORDS: Signal to noise ratio, Photodetectors, Digital signal processing, Imaging systems, Sensors, Luminescence, Photons, Signal processing, Charge-coupled devices, Acquisition tracking and pointing
We developed a simulation model of an integrated CMOS-based imaging platform for use with bioluminescent DNA microarrays. We formulate the complete kinetic model of ATP based assays and luciferase label-based assays. The model first calculates the number of photons generated per unit time, i.e., photon flux, based upon the kinetics of the light generation process of luminescence probes. The photon flux coupled with the system geometry is then used to calculate the number of photons incident on the photodetector plane. Subsequently the characteristics of the imaging array including the photodetector spectral response, its dark current density, and the sensor conversion gain are incorporated. The model also takes into account different noise sources including shot noise, reset noise, readout noise and fixed pattern noise. Finally, signal processing algorithms are applied to the image to enhance detection reliability and hence increase the overall system throughput. We will present simulations and preliminary experimental results.