UPDATED SC09: Resolution in Mobile Imaging Devices: Concepts and Measurements
Sunday 26 January • 13:30 – 15:30
Course Length: 2 hours
Course Level: Intermediate
Instructors: Uwe Artmann, Image Engineering GmbH & Co. KG, and Kevin J. Matherson, Microsoft Corporation

Learning Outcomes
This course enables the attendee to:

• Understand terminology used to describe resolution of electronic imaging devices.
• Describe the basic methods of measuring resolution in electronic imaging devices and their pros and cons.
• Understand point spread function and modulation transfer function.
• Learn slanted edge spatial frequency response (SFR).
• Learn Siemens Star SFR.
• Learn contrast transfer function.
• Understand human visual system resolution and perceptual resolution limits.
• Understand the difference between and uses of object space and image space resolution.
• Describe the impact of image processing functions on spatial resolution.
• Understand practical issues associated with resolution measurements.
• Understand targets, lighting, and measurement set up for visible and near-infrared resolution measurements.
• Learn measurement of lens resolution and sensor resolution.
• Appreciate RAW vs. processed image resolution measurements.
• Learn cascade properties of resolution measurements.
• Understand measurement of camera resolution.
• Understand the practical considerations when measuring real lenses.
• Specifying center versus corner resolution.
• Understand the impact of large distortion on slanted edge and Siemens star SFR.
• Learn about SFR measurement of wide angle lenses.
• Learn about impact of field curvature.
• Understand through-focus MTF.

This class is an update of our 2019 course and adds measurement of resolution in wide angles lenses as well as measurement of resolution in the near-infrared/infrared spectral regions. The course is of interest to those wanting to characterize cameras in AR/VR, automotive, machine vision, consumer, and mobile applications.

Resolution is often used to describe image quality of electronic imaging systems. Components of an imaging system such as lenses, sensors, and image processing impact the overall resolution and image quality achieved in devices such as digital and mobile phone cameras. While image processing can, in some cases, improve the resolution of an electronic camera, it can also introduce artifacts. This course is an overview of spatial resolution methods used to evaluate electronic imaging devices and the impact of image processing on the final system resolution. The course covers the basics of resolution and impacts of image processing, international standards used for the evaluation of spatial resolution, and practical aspects of measuring resolution in electronic imaging devices such as target choice, lighting, sensor resolution, and proper measurement techniques.

Intended Audience
Managers, engineers, and technicians involved in the design and evaluation of image quality of electronic cameras (regardless of application), video cameras, and scanners. Technical staff of manufacturers, managers of digital imaging projects, as well as journalists and students studying image technology.

Uwe Artmann studied photo technology at the University of Applied Sciences in Cologne following an apprenticeship as a photographer and finished with the German 'Diploma Engineer'. He is now the CTO at Image Engineering, an independent test lab for imaging devices and manufacturer of all kinds of test equipment for these devices. His special interest is the influence of noise reduction on image quality and MTF measurement in general.

Kevin Matherson is a director of optical engineering at Microsoft Corporation working on advanced optical technologies for AR/VR, machine vision, and consumer products. Prior to Microsoft, he participated in the design and development of compact cameras at HP and has more than 15 years of experience developing miniature cameras for consumer products. His primary research interests focus on sensor characterization, optical system design and analysis, and the optimization of camera image quality. Matherson holds a Masters and PhD in optical sciences from the University of Arizona.