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Proceedings Paper

Photo-response non-uniformity error tolerance testing methodology for CMOS imager systems
Author(s): Brent McCleary; Antonio Ortega
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Paper Abstract

An image sensor system-level pixel-to-pixel photo-response non-uniformity (PRNU) error tolerance method is presented in this paper. A scheme is developed to determine sensor PRNU acceptability and corresponding sensor application categorization. Many low-cost imaging systems utilize CMOS imagers with integrated on-chip digital logic for performing image processing and compression. Due to pixel geometry and substrate material variations, the light sensitivity of pixels will be non-uniform (PRNU). Excessive variation in the sensitivity of pixels is a significant cause of the screening rejection for these image sensors. The proposed testing methods in this paper use the concept of acceptable degradation applied to the camera system processed and decoded images of these sensors. The analysis techniques developed in this paper give an estimation of the impact of the sensor's PRNU on image quality. This provides the ability to classify the sensors for different applications based upon their PRNU distortion and error rates. The human perceptual criteria is used in the determination of acceptable sensor PRNU limits. These PRNU thresholds are a function of the camera system's image processing (including compression) and sensor noise sources. We use a Monte Carlo simulation solution and a probability model-based simulation solution along with the sensor models to determine PRNU error rates and significances for a range of sensor operating conditions (e.g., conversion gain settings, integration times). We develop correlations between industry standard PRNU measurements and final processed and decoded image quality thresholds. The results presented in this paper show that the proposed PRNU testing method can reduce the rejection rate of CMOS sensors. Comparisons are presented on the sensor PRNU failure rates using industry standard testing methods and our proposed methods.

Paper Details

Date Published: 19 January 2009
PDF: 12 pages
Proc. SPIE 7242, Image Quality and System Performance VI, 724216 (19 January 2009); doi: 10.1117/12.807557
Show Author Affiliations
Brent McCleary, Univ. of Southern California (United States)
Antonio Ortega, Univ. of Southern California (United States)

Published in SPIE Proceedings Vol. 7242:
Image Quality and System Performance VI
Susan P. Farnand; Frans Gaykema, Editor(s)

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