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IMPORTANT DATES

Call for Papers
» Journal-first (JIST or JPI)	15 May
» Conference	24 June
Acceptance Notification
» Journal-first (JIST or JPI)	30 June
» Conference	by 12 Aug
Final Manuscripts Due
» Journal-first (JIST or JPI)	15 Aug
» Conference	15 Sept

Registration Opens	by 31 Aug
Early Registration Ends	30 Sept
Conference Begins	13 Nov

CIC31 EDUCATIONAL PROGRAM

On this page

Short Courses by Day and Time
Short Course Descriptions
Workshops Descriptions
Short Course Fees

AT-A-GLANCE

CIC31 offers 15 courses—including 5 new courses—and 4 workshops. Courses require additional fees; workshops are complementary, but you still must register for them for planning purposes.

New Courses

SC02 Objective and Repeatable Color Capture in Scattering Media (Derya Akkaynak and Grigory Solomatov)
SC04 Color Naming Within and Across Languages (Dimitris Mylonas)
SC06 Material Appearance Measurement and Characterization (Yoko Arteaga)
SC07 Vivid Luminescence: Mastering Color & Color Rendition in LED Lighting (Michael J. Murdoch)
SC09 Color Image Analysis with Deep Learning: Techniques and Best Practices (Ahmed Mohammed and Marius Pedersen)
SC12 Color Imaging Challenges in AR, VR, and MR Imaging Systems (Kevin J. Matherson)

Workshops

W1: Color Grading for Digital Cinema (Charles Poynton and Laurens Orij)
W2: Challenges in Image Quality Assessment (Marius Pedersen and Seyed Ali Amirshahi)
W3: Material Appearance Measurement and Reproduction for Cultural Heritage Applications (Yoko Arteaga)
CANCELED W4: Display Simulation Pipeline for Augmented Reality (AR) (Christopher Reidy)

COURSES / WORKSHOPS BY DAY / TIME

Short course descriptions, including level, prerequisites, benefits, and instructor bios are found below the table. Workshops details, including speakers, are found below the Short Course descriptions.

Monday 13 November
8:00-10:00	10:15 -12:15	13:30-15:30	15:45-17:45
COLOR SCIENCE AND IMAGING FUNDAMENTALS
SC01: Color and Imaging Gaurav Sharma
CAMERAS AND GAMUTS			DEEP / MACHINE LEARNING
NEW SC02: Objective and Repeatable Color Capture in Scattering Media Derya Akkaynak and Grigory Solomatov		SC03: Color Gamut Mapping Jan Morovic	CANCELLED SC04: Color Naming Within and Across Languages Dimitris Mylonas
	WORKSHOP W01 (10:00 - 14:00) Color Grading for Digital Cinema Convenors: Charles Poynton and Laurens Orij
APPAMAT (additional fee)
Tuesday 14 November
8:00-10:00	10:15 -12:15	13:30-15:30	15:45-18:00
CAMERAS AND GAMUTS
SC05: Camera Color Characterization: Theory and Practice Eric Walowit and Dietmar Wueller		NEW SC12: Color Imaging Challenges in AR, VR, and MR Imaging Systems Kevin J. Matherson	WORKSHOP W02 Challenges in Image Quality Assessment Convenors: Marius Pedersen and Seyed Ali Amirshahi
MATERIAL APPEARANCE	DEEP/MACHINE LEARNING
NEW SC06: Material Appearance Measurement and Characterization Yoko Arteaga	NEW SC09: Color Image Analysis with Deep Learning: Techniques and Best Practices Ahmed Mohammed and Marius Pedersen	SC13: Deep Learning for Color Simone Bianco and Marco Buzzelli	WORKSHOP W03 Material Appearance Measurement and Reproduction for Cultural Heritage Applications Convenor: Yoko Arteaga
LIGHT / HDR / DISPLAYS
NEW SC07: Vivid Luminescence: Mastering Color & Color Rendition in LED Lighting Michael J. Murdoch	SC10: High-Dynamic-Range (HDR) Theory and Technology Alessandro Rizzi and John McCann	SC14: High Dynamic Range Imaging and Display - Technologies, Applications, and Perceptual Considerations Timo Kunkel	CANCELLED WORKSHOP W04 Display Simulation Pipeline for Augmented Reality (AR) Convenor: Christopher Reidy
ADVANCED COLOR	MATERIAL APPEARANCE	ADVANCED COLOR
SC08: Advanced Colorimetry and Color Appearance Gaurav Sharma	CANCELLED SC11: Measurement of Facial Appearance Using Imaging Technology Kaida Xiao	SC15: Color Spaces Research and Applications Ming Ronnier Luo

Short Course Descriptions

Monday 13 November

8:00 - 17:45 (8 hours)
Instructor: Gaurav Sharma, University of Rochester

SC01: Color and Imaging [+/–]

Level: Introductory

Prerequisites: High-school level familiarity with science and math concepts. Prior familiarity with basics of signal and image processing, in particular Fourier representations, is helpful although not essential for an intuitive understanding.

Benefits This course enables the attendee to:

Summarize the basic findings from color matching experiments and describe the concept of trichromacy.
Compute tristimulus values from spectral distributions and transform between commonly used color space representations.
Describe how color representations relate to the stages of the human visual system.
Discuss chromatic adaptation and its critical role in color perception.
Define the concept of a metamer and highlight the distinction between illuminant, observer, and device metamerism.
Explain the utility of uniform color spaces and color appearance attributes.
Outline the role that models of color perception play in imaging systems.
Infer the conceptual basis of commonly encountered color processing functions in imaging systems, such as white balance and gamma correction.

Course Description
This 8-hour course provides a comprehensive introduction to the fundamentals of color perception, measurement, and representation and an overview of how these play a role in modern imaging systems. It begins with a summary of the psychophysics of color: starting from spectral power distributions that form the physical basis of color, proceeding through successive stages of the human visual system, and culminating in the perceptual precepts of hue, saturation, and lightness. Elements of anatomy and physiology involved in these visual system stages are also briefly described in this context. Basic colorimetric and perceptual color representations rooted in the psychophysics of color are developed with a particular focus on the commonly used CIE standards, specifically, the CIEXYZ tristimulus space that is the basis of colorimetry and the CIELAB and CIELUV perceptually uniform color spaces. Chromaticity representations are covered as convenient 2D visualization tools. The course also includes a high-level overview of imaging systems that highlights the role played by models of color perception in their design and use.

Intended Audience: scientists, engineers, students, and managers involved in the design of color processing algorithms or color imaging systems.

Gaurav Sharma has more than 25 years of experience in the design and optimization of color imaging systems and algorithms that spans employment at the Xerox Innovation Group and his current position as a professor at the University of Rochester in the departments of electrical and computer engineering and of computer science. Additionally, he has consulted for several companies on the development of new imaging systems and algorithms. He holds 54 issued patents and has authored more than 200 peer-reviewed publications. He is the editor of the Digital Color Imaging Handbook (CRC Press) and served as the editor-in-chief for the SPIE/IS&T Journal of Electronic Imaging (2011-2015) and for the IEEE Transactions on Image Processing (2018-2020). Sharma is a fellow of IS&T, IEEE, and SPIE, and the IS&T Publications VP.

8:00 - 12:15 (4 hours)
Instructors: Derya Akkaynak and Grigory Solomatov, University of Haifa & Interuniversity Institute of Marine Sciences in Eilat

SC02: Objective and Repeatable Color Capture in Scattering Media [+/–]

Level: Introductory

Benefits This course enables the attendee to:

Learn which equation is appropriate to use in cases of attenuation i) in the atmosphere and ii) underwater.
Discover the variations commonly encountered in the optical conditions in the atmosphere and in natural bodies of water, and how these affect images.
Find out how to design an experiment or an image acquisition workflow so colors captured in a scene under a scattering medium can be used as scientific data.

Course Description
The most used image formation model is that for clear air, which is a non-attenuating medium. When we take photos in a medium that is attenuating, such as in haze or fog or in any natural body of water, the RGB values captured in a raw image no longer represent the radiance just from the scene; they also contain radiance added due to the scattering in the medium itself. The goal of this short course is to familiarize scientists and others working on color-sensitive applications with the equations that govern image formation in scattering media and to provide the tools needed for designing imaging experiments in scattering media so colors can be captured in an objective and repeatable manner and be used as scientific data.

Intended Audience: scientists, engineers, students, and others interested in learning more about capture and scattering.

Derya Akkaynak is assistant professor in the Marine Technologies Department at the University of Haifa, jointly with the Interuniversity Institute of Marine Sciences in Eilat. She has BSc and MSc degrees in aerospace engineering, and a PhD in mechanical and oceanographic engineering from the Massachusetts Institute of Technology. She leads the Laboratory for Computational Optics and Light in the Ocean Realm (COLOR Lab) in Eilat, conducting research on light, vision, and optics in the ocean.

Grigory Solomatov is currently a postdoctoral fellow at the Interuniversity Institute for Marine Sciences in Eilat, with an affiliation to Haifa University. His PhD was earned at the Technical University of Denmark, where he developed asymptotically fast algorithms in the fields of computer algebra and error-correcting codes. Currently, his research pivots towards leveraging techniques from optimization and machine learning to advance underwater computer vision and computational photography.

13:30 - 15:30 (2 hours)
Instructor: Ján Morovič, HP Inc.

SC03: Color Gamut Mapping [+/–]

Level: Introductory

Prerequisites: Knowledge of the fundamentals of colorimetry, color appearance, and color management is assumed.

Benefits This course enables the attendee to:

Understand the theory of color reproduction.
Identify the role and position of color gamut mapping in color reproduction.
Evaluate the performance of a color gamut mapping solution.
Choose from among the multitude of existing gamut mapping approaches.
Trace a color’s progress through a color reproduction workflow, with particular emphasis on the gamut mapping stage.
Consider future trends in color gamut mapping.

Course Description
Because different color reproduction media reproduce different ranges (gamuts) of colors, not all colors can be matched with all imaging devices. Reproducible colors therefore need to be found for all original colors, which is the role of gamut mapping. This course is based on the instructor’s Color Gamut Mapping book and recent advances in the field. It introduces color reproduction, makes the role of gamut mapping explicit, discusses how gamut mapping is implemented in commercial color management systems, and sketches out the variety of gamut mapping solutions proposed over the last forty years. Understanding the nature of gamut mapping provides a basis for making informed decisions about it when setting up color reproduction solutions.

Intended Audience: scientists, engineers, and creative content creators either designing or working with systems that reproduce color image content in various media; students in courses involving color and imaging components.

Ján Morovič is a Senior Color Scientist and Master Technologist at Hewlett-Packard’s Large Format Printing division in Barcelona, Spain. He has a BA (Hons) in print management from the London College of Printing and a PhD in color science from the University of Derby. Between 1998 and 2003 Ján was lecturer in digital color reproduction at the University of Derby’s Color and Imaging Institute and he also chaired the CIE’s Technical Committee on Gamut Mapping during this period. Since 2003, he has worked at HP on a variety of color reproduction technologies used in current products across their printer portfolio, including HP Pixel Control, HP Professional PANTONE Emulation, and HP CMYK Plus. He has published 118 peer–reviewed journal and conference papers, is the inventor of 141 granted US patents, and is the recipient of The Royal Photographic Society of Great Britain’s 2003 Selwyn Award.

15:45 - 17:45 (2 hours)
Instructor: Dimitris Mylonas, Northeastern University London

CANCELLED SC04: Color Naming Within and Across Languages [+/–]

Tuesday 14 November

8:00 - 12:15 (4 hours)
Instructors: Eric Walowit, consultant, and Dietmar Wueller, Image Engineering GmbH & Co. KG

SC05: Camera Color Characterization: Theory and Practice [+/–]

Level: Intermediate

Prerequisites: A basic understanding of color science.

Benefits This course enables the attendee to:

Understand the need for camera colorimetric characterization and the impact of color calibration on image quality and manufacturing yield.
Perform target-based and spectral-based camera characterization.
Solve for colorimetric camera transforms and build profiles using linear and nonlinear techniques.
Evaluate current colorimetric camera characterization hardware and software technology and products.
Participate in hands-on spectral camera characterization, camera transform generation, and matching from capture to display.

Course Description
This course covers the process of colorimetric camera characterization in theory and practice. The need for camera characterization and calibration and the impact on general image quality is first reviewed. Known issues in traditional approaches are discussed. Methodology for building camera colorimetric transforms and profiles are detailed step-by-step. State-of-the-art solutions using current technology are presented including monochromators, multispectral LED light sources, in situ measurements of spectral radiances of natural objects, and modern color transform methods including multidimensional color look up tables. A live demonstration is performed of the end-to-end process of spectral camera characterization, camera transform generation, and matching from capture to display. This course provides the basis needed to implement advanced color correction in cameras and software.

Intended Audience: engineers, project leaders, and managers involved in camera image processing pipeline development, image quality engineering, and production-line quality assurance.

Eric Walowit’s interests are in color management, appearance estimation, and image processing pipelines for digital photographic applications. He is the founder (retired) of Color Savvy Systems, a color management hardware and software company. He graduated from RIT’s image science program, concentrating in color science. Walowit is a member of ICC, ISO/TC42, IS&T, and CIEJTC10.

Dietmar Wueller studied photographic sciences in Cologne. He is the founder of Image Engineering, one of the leading suppliers of test equipment for digital image capture devices. Wueller is a member of IS&T, DGPH, and ECI, and he is the German representative for ISO/TC42/WG18; he also participates in several other standardization activities.

8:00 - 10:00 (2 hours)
Instructor: Yoko Arteaga, Norwegian University of Science and Technology (NTNU)

SC06: Material Appearance Measurement and Characterization [+/–]

Level: Introductory

Prerequisites: A technical background is not required, but an understanding of basic scientific principles will be very helpful.

Benefits This course enables the attendee to:

Gain basic theoretical knowledge on appearance, as well as the practical implications of appearance measurement.
Understand the perceptual nature of appearance and its implications.
Understand the different appearance attributes (color, gloss, translucency, and texture) and how to measure each one.
Understand differences between data obtained by appearance capture devices (including imaging methods).
Interpret measurement results and the implications of various appearance attributes.
By the end of the course, attendees are able to identify, plan, and evaluate different scenarios where appearance measurement and characterization play a significant role. Examples from the cultural heritage and other fields are provided.

Course Description
Objects exist in a wide range of materials with unique appearances. As such, it is vital that their appearance is properly measured and analysed. However, appearance is a complex perceptual property that entails four main attributes: color, gloss, translucency, and texture. Moreover, in collaborative and multidisciplinary fields, consistent terminology is vital. For these reasons this course aims to provide a basic theoretical introduction to appearance concepts such as the perceptual nature of appearance, measurable appearance attributes, the technologies and equipment available to measure appearance, and a basic overview of different evaluation methods. Appearance acquisition devices, including imaging devices, are presented, as is the different information obtained by each of them. Please note, this course does not provide details on the principles behind the acquisition methods.

Intended Audience: scientist, engineers, and others interested in learning more about the topic. Participants develop an increased understanding of different terminology related to appearance, measurement, visualization, reproduction, etc.

Yoko Arteaga is a postdoctoral researcher at the Colorlab at the Norwegian Univerisity of Science and Technology. Her research focuses on developing techniques to measure and model material appearance for cultural heritage objects. She is mainly interested in challenging materials such as gold and gilding, as well as material perception and the influence of fabrication methods. She has a background in physics and color science.

8:00 - 10:00 (2 hours)
Instructor: Michael J. Murdoch, Munsell Color Science Laboratory, Rochester Institute of Technology

SC07: Vivid Luminescence: Mastering Color & Color Rendition in LED Lighting [+/–]

Level: Introductory

Prerequisites: Familiarity with basic colorimetry and linear algebra is helpful, but not essential.

Benefits This course enables the attendee to:

Identify and compare LED color architectures, including phosphor-converted blue pump (PC-white), tunable white, RGB, RGBW, and addressable multiprimary systems.
Understand important visual characteristics of light: luminous flux, intensity distribution, color, CCT, and color rendition.
Evaluate color rendition, or how spectral characteristics of “white” LEDs affect rendered object colors and what this means for perceived naturalness and preference.
Compute and apply color rendition measures including TM-30 Rf, Rg, Rcs, etc.
Compute composite spectral power distributions from discrete LEDs to meet colorimetric aims and additional optimization goals.
Evaluate the melanopic and chronobiological responses (such as those on circadian rhythms) of spectral power distributions of light.

Course Description
LED lighting is one of the most impactful visual technologies available, offering near-limitless options in spectral power distribution to light up our world. But, how much do you know about light-emitting diodes (LEDs), how they make “white” light, and how strongly they can affect object colors? This course gives you the skills to evaluate what “good” color in LED lighting means and how to create it. Through phosphor combinations and multichannel systems, spectral characteristics can be tuned to mimic standard illuminants, maximize fidelity, naturalness, or preference for object color rendition, and to influence circadian rhythms. This course explains and shows many examples of the essential characteristics of color, color rendition, chronobiology, and quality of light in solid-state (LED and OLED) lighting. While mostly lecture with detailed notes, the course also includes demos and examples of Matlab- and Python-based lighting computations.

Intended Audience: scientists, engineers, and students using LED lighting systems for research, image capture, or image/product evaluation, and anyone who wants to know more about characteristics of quality LED and OLED lighting.

Michael J. Murdoch is an associate professor in RIT’s Munsell Color Science Laboratory, where he teaches colorimetry, imaging, and lighting topics. His research addresses temporally dynamic lighting, perception of advanced displays, and color appearance in augmented reality. Murdoch’s experience with color perception and color system design includes industrial research at Kodak Research and Philips Research, as well as his education at Cornell, Rochester Institute of Technology, and Eindhoven University of Technology.

8:00 - 10:00 (2 hours)
Instructor: Gaurav Sharma, University of Rochester

SC08: Advanced Colorimetry and Color Appearance [+/–]

Level: Intermediate

Prerequisites: Prior knowledge of fundamentals of colorimetry is assumed. The presumed background is at the level covered in CIC SC01 Color and Imaging.

Benefits This course enables the attendee to:

Explain how changes in the state of visual adaptation affect the perceived appearance of colors.
List the main elements of a color appearance model and explain the critical role of chromatic adaptation.
Describe the Von Kries framework commonly employed for chromatic adaptation transformations and perform computations using the model.
Explain how the CIECAM02/CAM16 color appearance models compute color appearance correlates from colorimetry and viewing condition specifications and to obtain corresponding colorimetric representations for different viewing conditions.
List commonly employed color appearance models and explain how relevant parameters for these models are determined for real-world viewing environments.
Describe the components of spatial color appearance models and highlight the interactions between color and spatial perception.

Course Description
Building upon a foundation in basic color science and colorimetry, this course provides attendees with a broad understanding of color appearance phenomena and introduces them to color appearance modeling. Several important color appearance phenomena are presented and their relation to changes in the state of adaptation of the human visual system is explained. The perceptual color attributes of lightness, brightness, colorfulness, saturation, chroma, and hue are defined and explained. Common computational models for evaluating correlates of these attributes are presented. Spatial aspects of color vision are discussed and simple models for spatial color perception are summarized.

Intended Audience: color engineers, research scientists, and software developers involved in design and optimization of color imaging systems, algorithms, and devices.

Gaurav Sharma has more than 25 years of experience in the design and optimization of color imaging systems and algorithms that spans employment at the Xerox Innovation Group and his current position as a professor at the University of Rochester in the departments of electrical and computer engineering and of computer science. Additionally, he has consulted for several companies on the development of new imaging systems and algorithms. He holds 54 issued patents and has authored more than 200 peer-reviewed publications. He is the editor of the Digital Color Imaging Handbook (CRC Press) and served as the editor-in-chief for the SPIE/IS&T Journal of Electronic Imaging (2011-2015) and for the IEEE Transactions on Image Processing (2018-2020). Sharma is a fellow of IS&T, IEEE, and SPIE, and the IS&T Publications VP.

10:15 - 12:15 (2 hours)
Instructors: Ahmed Mohammed, SINTEF and NTNU, and Marius Pedersen, NTNU

SC09: Color Image Analysis with Deep Learning: Techniques and Best Practices [+/–]

Level: Introductory

Prerequisites: Familiarity with Python programming. Students are required to bring a laptop with Colab (https://colab.google/) loaded and set up prior to the course. To use Colab you will need a Google account. Students should familiarize themselves with the following Source Code References:

https://pytorch.org/tutorials/beginner/transfer_learning_tutorial.html
Color classification: https://www.kaggle.com/datasets/ayanzadeh93/color-classification
Apples vs orange: https://drive.google.com/file/d/1WrCRsn46SckAL43GssZizqkQ_IbxCVgM/view

Benefits This course enables the attendee to:

Build a foundation in deep learning that can be applied to a wide range of fields, including computer vision, natural language processing, and robotics.
Gain knowledge of best practices for handling color data in deep learning to improve model performance and accuracy.
Understand how to pre-process color images for deep learning tasks.

Course Description
This course is a concise and focused on hands-on introduction to deep learning with PyTorch, covering the basics of pre-processing color images and applying convolutional neural networks (CNNs) for color image classification. The course is organized as 25% theory and 75% practical. It covers topics such as transfer learning for color image analysis, and the effects of texture, color, and shape biases in deep learning. Best practices for handling color data in deep learning are also discussed. The course includes six modules, each ranging from 10 to 30 minutes in length, that provide an overview of the key concepts and techniques used in modern deep learning applications.

Intended Audience: individuals interested in a hands-on experience with deep learning, particularly with a focus on color image analysis. This could include students, researchers, and professionals in fields such as computer science, engineering, and data science.

Ahmed Mohammed received his master’s degree in electronics and information engineering from Chonbuk National University in South Korea and PhD in computer science from the Norwegian University of Science and Technology (NTNU). He is currently a research scientist at SINTEF Digital and an adjunct associate professor with NTNU. His research interests include machine learning and computer vision, with emphasis on medical imaging and 3D vision for explainable and data-efficient learning.

Marius Pedersen has a bachelor’s degree in engineering data and master’s degree in technology and media engineering from Gjøvik University College. He received his PhD in color image technology from the University of Oslo. Pedersen is professor in the Department of Computer Technology and Informatics at NTNU, where he is also head of the Colorlab. His work is aimed at quality assessment of images with classical and deep learning approaches.

10:15 - 12:15 (2 hours)
Instructors: Alessandro Rizzi, Università degli Studi di Milano

SC10: High-Dynamic-Range (HDR) Theory and Technology [+/–]

Level: Introductory

Prerequisites: Knowledge of the fundamentals of colorimetry, color appearance, and color management is assumed.

Benefits This course enables the attendee to:

Measure the optical limits in acquisition and display; in particular measure the scene dependent effects of optical glare.
Compare the accuracy of scene capture using single and multiple-exposures in normal and RAW formats.
Engage in a discussion of human spatial vision that responds to the retinal image altered by glare.
Engage in a discussion of current HDR TV systems and standards: tone-rendering vs. spatial HDR methods.
Explore the history of HDR imaging.

Course Description
To understand HDR imaging is to understand the properties and limitations of the Artist’s Goal, the Calculated Sensation Goal, and the Accurate Scene Radiance Goal. This course emphasizes measurements of physics (accurate reproduction) and psychophysics (visual appearance). Physics shows limits caused by optical glare; HDR does not reproduce scene radiances. Psychophysics shows that human vision’s spatial-image-processing renders scene appearance.

The course reviews successful HDR reproductions; limits of radiance reproduction; HDR TV’s technology and standards; appearance and display luminance; and appearance models. HDR technology is a complex problem controlled by optics, signal-processing, and visual limits. The solution depends on its goal: physical information or preferred appearance.

Intended Audience: anyone interested in using HDR imaging: science, technology of displays, and applications. This includes students, color scientists, imaging researchers, medical imagers, software and hardware engineers, photographers, cinematographers, and production specialists.

Alessandro Rizzi is a full professor in the department of computer science at the University of Milano. He is one of the founders of the Italian Color Group, secretary of CIE Division 8, and an IS&T Fellow and past vice president. In 2015, he received the Davies medal from the Royal Photographic Society. He is co-chair of the Color Imaging: Displaying, Processing, Hardcopy, and Applications Conference at the IS&T Electronic Imaging Symposium; topical editor for the Journal of Optical Society of America; and associate editor of Journal of Electronic Imaging.

John McCann worked in, and managed, Polaroid’s Vision Research Laboratory for 35 years. He studied Retinex theory, color constancy, color from rod/cone interactions at low light levels, image reproduction, appearance with scattered light, cataracts, and HDR imaging. He is a Fellow of IS&T and Optica (formerly OSA); a past president of IS&T and the Artists Foundation, Boston; the IS&T/OSA 2002 Edwin Land Medalist, an IS&T 2005 Honorary Member, and the AIC 2021 Judd Medalist.

10:15 - 12:15 (2 hours)
Instructor: Kaida Xiao, University of Leeds

CANCELLED SC11: Measurement of Facial Appearance Using Imaging Technology [+/–]

13:30 - 15:30 (2 hours)
Instructor: Kevin J. Matherson, Microsoft

SC12: Color Imaging Challenges in AR VR and MR Imaging Systems [+/–]

Level: Intermediate

Benefits This course enables the attendee to:

Understand the fundamental challenges posed by compact camera optics on color image processing.
Specify the color corrections required to compensate for compact camera optics limitations.
Understand current optical components and sub systems, as well as their limitations, in head mounted displays used for consumer applications.
Describe tradeoffs and relations between metrics such as field of view, MTF, and eyebox size, based on display and camera architecture choice.
Evaluate ISP-based solutions to correct chromatic aberrations and color shading in compact camera systems and display optics.

Course Description
This course describes the color imaging challenges created by the unique characteristics of compact camera and display optics used in AR, VR, MR, automotive, machine vision, and consumer applications. These devices have to satisfy stringent requirements in terms of size, weight, and power while still delivering high-quality senor, camera, and display imagery. First, the fundamentals of small-format camera optics are introduced; the lack of choice of suitable materials and steep chief ray angles results in a spatially-varying spectral sensitivity must be calibrated out to avoid color shading. Next, we review the components and optics of head mounted displays with an emphasis on how the choice of architecture can result in a compact system that still delivers comparable optical performance in a smaller form factor. The course gives the attendee an understanding of the physics and interaction of light, camera optics, display optics, and color, as well as the algorithmic foundations for image signal processors in which the optics and ISP are jointly designed with the goal of improving the overall system image quality.

Intended Audience: engineers, project leaders, and managers involved in camera image processing, pipeline development, image quality engineering, production-line quality assurance, and those who want to understand the challenges of compact optics used in miniature camera and display systems.

Kevin J. Matherson is a director of optical engineering at Microsoft Corporation working on advanced optical technologies for 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 a PhD in optical sciences from the University of Arizona.

13:30 - 15:30 (2 hours)
Instructors: Simone Bianco and Marco Buzzelli, University of Milano-Bicocca

SC13: Deep Learning for Color [+/–]

13:30 - 15:30 (2 hours)
Instructor: Timo Kunkel, Dolby Labs, Inc.

SC14: High Dynamic Range Imaging and Display - Technologies, Applications, and Perceptual Considerations [+/–]

Level: Introductory

Prerequisites: No direct previous knowledge is required, but a basic understanding of traditional display and imaging concepts is beneficial.

Benefits This course enables the attendee to:

Understand todays HDR ecosystem elements from capture via production and distribution to content display.
Reassess how the human visual system (HVS) perceives the physical world around us and identify how we can reproduce a plausible depiction of this ‘real’ physical world, including artistic intent.
Identify how HDR display technologies cater to these requirements and what aspects can be improved in the future.
Explain the fundamentals of common HDR and Wide Color Gamut display technologies such as full array dual modulation, OLED, Quantum Dot, and Mini/MicroLED-based display.
Differentiate the considerations for creating compelling content that lives up to the capabilities of HDR displays.

Course Description
High-Dynamic Range imaging, better known by its acronym “HDR”, has established itself as a foundational component when looking at the aspects defining today’s image fidelity. HDR technology is widely supported by millions of devices from cameras to post-production tools, deployment systems, and displays and is embraced by content creators and providers. HDR imaging is based on several key concepts that facilitate perceptually-meaningful, artistically-compelling, and technologically-effective delivery of movies, TV shows, and video games that are more immersive and realistic than previously possible. This course provides an overview of concepts enabling the HDR ecosystem elements of today and discusses challenges that remain to be solved. This includes perceptual and technological aspects, as well as industry standards, formats, and approaches.

Intended Audience: anyone working in image display related fields such as display design, content creation, image transport and broadcast, and vision science.

Timo Kunkel is director of image technology & standards in the CTO office of Dolby Labs, Inc. During the past 15 years he has been investigating the technical and perceptual aspects of HDR and wide color gamut imaging with a focus on advanced display approaches. He also has been involved in developing the core concepts of what is now Dolby Vision. Kunkel has published and taught about HDR concepts and technologies throughout the industry for many years. He is a member and technical expert with ICC, SID ICDM, and IEC TC100 and 110. Kunkel holds a PhD in computer science from University of Bristol, UK, and a MSc from University of Freiburg, Germany.

13:30 - 15:30 (2 hours)
Instructor: Ming Ronnier Luo, Zhejiang University

SC15: Color Spaces Research and Applications [+/–]

Level: Intermediate

Benefits This course enables the attendee to:

Learn about techniques for visually assessing color difference.
Understand the techniques for performing image processing.
Discover the techniques for image quality assessment in the imaging industry.

Course Description
The course introduces techniques to achieve robust data to investigate two aspects of color space, space uniformity (SU) and hue linearity (HL). The former specifies color differences in different color centres. The latter defines the colors having the same hue perception along the chroma direction. However, the spaces developed from those data cannot predict both SU and HL groups of data accurately. New efforts are introduced to develop satisfactory spaces with simple structure and accurate predictions to both data groups. Finally, a demonstrator shows structure of a color space in terms of 1D scales (lightness, chroma, and hue), and 2D scales (depth and vividness). Images are used to show the appearance change according to these scales..

Intended Audience: color engineers and research scientists involved with color reproduction, imaging device developers, and computer software developers. Knowledge of fundamental colorimetry is assumed.

M. Ronnier Luo is a professor at the College of Optical Science and Engineering in Zhejiang University (China). He received his PhD from the Bradford University (UK) in color science and has published more than 750 peer reviewed papers in the fields of color science, imaging science, and illumination engineering. He is a Fellow IS&T and the Society of Dyers and Colorists. Luo has been an active member of the International Commission on Illumination (CIE), ex-Vice President, ex-Division Director on Color and Vision, and Technical chair. He has also closely collaborated with more than 20 leading companies to develop innovative technologies. Luo has received numerous awards, including the 2017 Judd Award from the International Color Association (AIC), and the 2020 Newton Award from the Color Group of the Great Britain for his contribution in color science research.

Workshop Descriptions

Monday 13 November

10:00 – 14:00
Conveners and Speakers: Charles Poynton, independent researcher and Laurens Orij, Crabsalad

Color Grading for Digital Cinema [+/–]

Tuesday 14 November

15:45 – 18:00
Conveners: Marius Pedersen, Colourlab director and professor, and Seyed Ali Amirshahi, associate professor, NTNU

Challenges in Image Quality Assessment [+/–]

15:45 – 18:00
Convener: Yoko Arteaga, NTNU / Moderator: Jon Yngve Hardeberg, NTNU

Material Appearance Measurement and Reproduction for Cultural Heritage Applications [+/–]

Description
This workshop explores the perspectives and challenges of material appearance measurement and reproduction in the field of cultural heritage. Cultural heritage materials exist in an infinite variety of appearances, depending not only on the physical properties of the materials themselves, but also on the fabrication methods, artistic decisions, and contextual parameters of the object. All these parameters influence the final visual perception of the cultural heritage object. Thus, there are many challenges when it comes to accurately measuring and reproducing material appearance properties. This workshop takes the form of an interactive panel discussion with experts from different fields. The topics discussed are the needs from cultural heritage professionals such as conservators, the possibilities in cultural heritage research, and perspectives in material appearance reproduction for cultural heritage. Samples will be shown and the audience is highly encouraged to participate by asking questions and engaging in the discussions.

Speakers

Yoko Arteaga, NTNU (Norway)
Clotilde Boust, C2RMF (France)
Stephanie Courtier, C2RMF (France)
Christophe Leynadier, Mihaly Group (France)

Yoko Arteaga is a postdoctoral researcher in the Colorlab at the Norwegian University of Science and Technology. Her research focuses on developing techniques to measure and model material appearance for cultural heritage objects. She is mainly interested in challenging materials such as gold and gilding, as well as material perception and the influence of fabrication methods. She has a background in physics and color science.

Clotilde Boust is head of the Imaging Department at the Centre for Research and Restoration of the Museums of France (C2RMF). Her main interests are colour imaging, scientific imaging, and 3D imaging for conservation.

Stephanie Courtier is a gilded wood restorer at C2RMF. Her main interest is in scientific methods applied to conservation and restoration.

Christophe Leynadier is president and co-founder of the Mihaly Group. His area of expertise is appearance reproduction using 2.5D printing.

15:45 – 18:00
Convener and Speaker: Christopher Reidy, Meta Platforms, Inc.

CANCELLED Display Simulation Pipeline for Augmented Reality (AR) [+/–]

Short Course Fees

	Through 22 October			Starting 23 October
	Member	Non-Member	Student	Member	Non-Member	Student
8-hour course (SC01)	$525	$575	$195	$575	$625	$220
4-hour courses (SC02 and SC05)	$330	$355	$95	$380	$405	$120
2-hour courses	$200	$225	$65	$250	$275	$90
Take 3 or more courses and receive 10% discount. Use Coupon Code 2023PICK3 at checkout.

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