Course 013 Digital Imaging: Image Capturing, Image Sensors – Technologies and Applications
Available course dates
This course has no planned course dates.
If you are interested in this course, contact us at cei@cei.se
TECHNOLOGY FOCUS
New developments in CMOS Semiconductor Technology, next to the outstanding imaging performance of solid-state imagers, open up new applications.
Automotive camera systems, improving image quality, and post-capture image processing techniques for digital video signals are important areas where extensive development progress is being made. It is just a matter of time before we will detect single photons with solid-state image sensors, enabling photon counting applications which enable quality images in extremely low light conditions.
In the medical world, new surgery techniques become possible thanks to the powerful characteristics of the image sensors. Also in the mobile world, the image sensor technology went to a revolution over the last two decades. For instance, in a today’s smart phone, there are more mm2 of imaging silicon than in a professional broadcast camera.
COURSE CONTENT
The major objective of this course is to make the participants familiar withSolid-State Imaging and the relevant related topics.
It will give an in-depth view of the possibilities and limitations of the image capturing technology of today and tomorrow.
Participants will receive a comprehensive set of course notes. These notes are for participants only and are not for sale.
WHO SHOULD ATTEND
The course is aimed at engineers, scientists and managers with basic knowledge, either theoretical or hands-on, in engineering or physics.
No detailed knowledge of device physics is assumed.
The course is developed to give an in-depth understanding of image capturing to engineers and technicians who are active in the field, and to give those with a theoretical knowledge the opportunity to learn more about the practical issues of the subject.
Much of the course will be of interest also to camera designers through its practical approach.
The course will provide managers and research workers having related experience in industrial, governmental or academic institutions with a valuable update on the latest developments in this fast-moving imaging topics.
More experienced engineers should instead choose our course No. 020 Advanced Course on Imaging Sensor Technology.
Daily Schedule
Day 1
During the first day of the course, we will focus on the overall image sensor architecture and the various pixels used in CMOS image sensors. Pixels with 1 transistor, 3 transistors and eventually 4 transistors will be explained. The pixel discussion will be concluded with the shared pixel concept.
Without any further introduction it should be clear that light sensitivity is an important characteristic of the devices. In the course, the light sensitivity of the sensors will be explained, and (new) technologies will be introduced on how to further increase the light sensitivity.
Day 2
The second day of the class will be a very “noisy” day. The full day will be devoted to noise. Special attention will be paid to temporal noise sources and to fixed-pattern or spatial noise sources. Once the various noise issues are understood, the focus will shift to how to mitigate (most of) the noise generated by all the various sources.
The second day will conclude with the perception of noise in images by the human visual system and with an in-depth discussion about signal-to-noise ratio and how manipulation of images will change the signal-to-noise ratio.
Day 3
Once the basics of the image sensors are clear, as well as sensitivity and noise is explained, the time will come to characterize all those parameters. Characterization of the following parameters will be discussed: temporal noise (total, column, row, pixel), fixed-pattern noise (total, column, row, pixel), dark current, light sensitivity, quantum efficiency, photo-response non-uniformity, image lag.
A very special performance characteristic of an image sensor is the modulation transfer function (MTF). Why is MTF important, and how is it measured?
Day 4
The last day of the class will be devoted to special architectures that are used to improve the characteristics of the devices. Examples of these architectures are color image sensors, devices for wide dynamic range, imagers with global shutter pixels, time-of-flight devices, phase-detection auto-focus pixels, …
The training will be concluded with a quick look at datasheets. What is specified in a data sheet and what is not specified? What are the traps that are present in a data sheet?
ALL COURSE DATES FOR THE CATEGORY: Sensors and Digital Imaging
014 Digital Camera Systems
020 Advanced Course on Image Sensor Technology
063 Advanced Optical Sensors: From Detectors to ASIC Integration with Edge AI and Functional Safety Considerations
Instructor: Dr. Farzad Parsaie
Optical sensors are evolving toward intelligence, downsizing, and multi-functionality, with critical roles in functional safety applications like autonomous driving, industrial automation, and medical diagnostics. Artificial Intelligence (AI) is enhancing optical sensor performance by improving data processing, signal-to-noise ratios, and handling dynamic scenarios, essential for high-fidelity measurements in these fields. This course covers these advancements, from photodetector fundamentals to ASIC integration and interfacing, with a focus on Edge AI and Functional Safety. Read full course description including course schedule063 Advanced Optical Sensors: From Detectors to ASIC Integration with Edge AI and Functional Safety Considerations
063 Advanced Optical Sensors: From Detectors to ASIC Integration with Edge AI and Functional Safety Considerations
835 A 360-degree View of the Sensors for Industrial Applications – Focusing on the Inductive Sensors
He is a new instructor of the CEI-Europe and is a professional expert on the subject of design and manufacturing of electronic sensors and ASIC designing, testing, and release for such products. After more than 25 years with one of the 10 global players on the field of industrial sensors – Balluff GmbH Company, Germany – he is currently as a freelancer in his consulting office FerSensC / Leonberg, Germany, carrying out sensor design projects and consulting.
Read full course description including course scheduleE-Course 601 Introduction to Correlated and Uncorrelated Noise in Imagers
Instructor: Professor Albert J.P Theuwissen
Introduction to Correlated and Uncorrelated Noise in Imagers In the introduction of the course, the difference between Correlated and Uncorrelated Noise will be explained. In a first instance, one can put all fixed-pattern noise sources or noise in the spatial domain under the header of Correlated Noise, and one can put all temporal noise sources or noise in the time domain under the header of Uncorrelated Noise. The course includes:- 42 minutes on-demand video
- 9 modules
- 3 months access
E-Course 602 Characterization of Noise in Dark
Instructor: Professor Albert J.P Theuwissen
Characterization of Noise in Dark It may sound strange that an image sensor, which is made to capture light, will be characterized first in dark conditions. But actually this should not really be surprising because noise will first become visible in the darkest parts of an image. For that reason the dark performance of an image sensor plays crucial role. It also sets the lower end of the dynamic range…… The course includes:- 116 minutes on-demand video
- 37 modules
- 3 months access
E-Course 603 Characterization of Noise with Light
Instructor: Professor Albert J.P Theuwissen
Characterization of Noise with Light In the third and last part of the course, the image sensor will be characterized with light input. First the fixed-pattern noise (= correlated noise) will be measured, and next the temporal noise (= uncorrelated noise) will be characterized. All measurements will be based on an existing camera and with uniform light input. For both noise types, correlated and uncorrelated, some extra statistical operations will allow to split the overall noise characterized into a contribution on row level, on column level and on pixel level. This gives very useful information on where to find the root cause of the noise sources. The course includes:- 126 minutes on-demand video
- 34 modules
- 3 months access
E-Course Bundle 601-603 Advanced course in image sensors and digital cameras
Instructor: Professor Albert J.P Theuwissen
The course includes:- 284 minutes on-demand video
- 80 modules
- 12 months access