Brent McCleary

Bio: Brent McCleary is an academic researcher from University of Southern California. The author has contributed to research in topics: Pixel & Pixel geometry. The author has an hindex of 1, co-authored 1 publications receiving 3 citations.

Photo-response non-uniformity error tolerance testing methodology for CMOS imager systems

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.

CCD imagers MTF enhanced filter design

Abstract: In order to improve the imaging quality of the optical imagers, the modulation transfer function enhanced CCD signal filter circuit is designed. Firstly, the imager MTF transfer chain is discussed, and the impact to MTF causing by each part of imaging chain is introduced. Secondly, from frequency domain and time domain respectively the MTF enhanced filter principle and implementation method are analyzed, the filter minimum bandwidth is confirmed. By comparing the step response of the filter and the response of the camera to the Nyquist spatial frequency fringe imaging in simulation experiment, the optimum quality factor of the MTF enhancement filter is determined. Lastly, the camera MTF test was carried out using black and white stripe target, and the SNR of the camera was measured by integrating sphere. The test results show that MTF enhanced filter can improve the system MTF 30% when the quality factor is 1, and the noise suppression capability is comparable to that of the maximally flat filter in the pass-band. MTF enhancement filter can effectively improve the imaging performance of CCD camera.

Study of V/Q Non-Linearity in Scientific CMOS Sensor

Abstract: Scientific CMOS sensor usually manifests V/Q non-linearity in charge-to-voltage conversion. Starting from the mechanism underlying this non-linearity, we build the V/Q non-linearity model to study the influence of modulation transfer function (MTF) and signal-to-noise ratio (SNR). Meanwhile, simulation verification is carried out. The results show that V/Q non-linearity improves SNR but causes the decrease of MTF of the electronic device. We propose the combination of video response curve with photo response non-uniformity (PRNU) noise curve to locate V/Q non-linearity. The validity of this method is proved by simulation verification and physical experiment. The present study provides reference for design optimization and compensation for non-linearity in scientific CMOS sensor.

PRNU Estimation of Linear CMOS Image Sensors That Allows Nonuniform Illumination

Abstract: Photo response nonuniformity (PRNU) is a crucial parameter in evaluating and choosing CMOS image sensors. The current methods and standards use the integrating sphere to illuminate the sensor and assume a known uniform illumination. And PRNU is calculated based on the spatial variance of images. In practice, the uniformity of illuminance can be hardly guaranteed. A slight nonuniformity will cause a significant increase in spatial variance and bring unacceptable evaluation errors. In this article, we present a novel method to estimate PRNU of linear CMOS image sensors. The method allows nonuniform illumination and does not require specific settings for the light source and sensors. First, an observation model is established for the data of nonuniformly exposed images. The model is composed of an irradiance model and a noise model. The irradiance model describes the original output, and the noise model depicts the noise variance as a function of local illuminance. PRNU is a parameter in the noise model to be estimated. Then, the model parameters including PRNU are estimated by a two-stage method based on maximum likelihood estimation. We also use simulations to validate the developed methods and demonstrate the robustness of the model under sensor misalignment. Finally, the proposed method is illustrated by a measurement experiment.