A 1-Day Short Course
Photon transfer (PT) is a popular and essential characterization standard employed in the design, operation, characterization, calibration, optimization, specification, and application of digital scientific and commercial camera systems. The PT user-friendly technique is based on only two measurements: average signal and rms noise, which together produce a multitude of important data products in evaluating digital camera systems (most notably CCD and CMOS).
PT is applicable to all imaging disciplines. Design and fabrication process engineers developing imagers rely heavily on PT data products in determining discrete performance parameters, such as quantum efficiency (QE), quantum yield, read noise, full well, dynamic range, nonlinearity, fixed pattern noise, V/e-conversion gain, dark current, image, etc. Camera users routinely use the PT technique to determine system-level performance parameters to convert relative measurements into absolute electron and photon units, offset correction, flat field and image S/N, ADC quantizing noise, optimum encoding, minimum detectable luminance, operating temperature to remove dark current, reliability, stability, etc. PT also is the first go/no-go test performed to determine the health of a new camera system and/or detector, as well as provide a power tool in troubleshooting problems.
This one-day course reviews these aspects and many others offered by photon transfer. Intended for engineers, scientists, and technical managers working with commercial and scientific digital camera systems.
- Describe PT theory
- Take PT data and determine important CCD and CMOS performance parameters
- Show example PT data products generated by CCD and CMOS imagers
- Calibrate a camera system in absolute physical units
- Use PT to determine the best camera or CCD/CMOS imager for the application
- Use PT to demonstrate and verify the camera system is reliable and in good operating order
- Discuss guidelines for the novice and advanced user in generating PT, modulation, and lux transfer curves
- Use PT to optimally remove fixed pattern noise sources in images for the highest S/N possible through flat fielding
- Comprehend signal-to-noise image theory through PT
Some familiarity with CCD and CMOS imagers is recommended.
The text, Photon Transfer, James R. Janesick (SPIE Press, 2007), and lecture notes are distributed on the day of the course. The notes are for participants only and are not for sale.
Coordinator and Lecturer
James R. Janesick, MSEE, Director, CMOS Advanced Development Group, Sarnoff Corporation, Huntington Beach, California. Mr. Janesick was previously with Conexant Systems Inc., developing CMOS imaging arrays for commercial applications. He was technology director of Pixel Vision, Inc. for five years, developing high-speed backside-illuminated CCDs for scientific and cinema cameras. Prior to this, Mr. Janesick was with the Jet Propulsion Laboratory for 22 years, where as group leader he designed scientific ground and flight-based imaging systems. He has authored 75 publications and has contributed to many NASA Tech Briefs and patents for various CCD and CMOS innovations. Mr. Janesick received NASA medals for Exceptional Engineering Achievement (1982 and 1992) and was the recipient of the SPIE Educator Award (2004) and was SPIE/IS&T Imaging Scientist of the Year (2007).
- Review photon transfer (PT) history and application
- Understand photon and particle interaction, photoelectric effect, quantum efficiency, and yield
- Describe fundamental solid-state imager noise sources (e.g, read noise, photon shot noise, signal noise, fixed pattern noise, fano noise) and their association to PT
- PT theory and the PT relation
- PT curve (PTC) set-up for laboratory generation, PTC families, Variance PTC, common PTC errors, measurement accuracy, and experimental data
- Measuring V/V and V/e-nonlinearity with PTC
- Using the Flat Fielding technique to remove fixed pattern noise with PTC calibration
- Introduce MTF, image contrast, and the Modulation PTC (MPTC) to measure signal information contained in images
- Signal-to-noise (S/N) performance of images using PTC and MPTC
- Present the Lux Transfer Curve (LTC) and Modulation Lux Transfer curve (MLTC) to determine absolute S/N performance of images
- Common read noise sources characterized by the PT technique
- Step-by-step PTC experiment data reduction and simulation examples
For more information contact the Short Course Program Office:
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