October 29, Tuesday, 10:15 - 12:15 (2 hours)

Instructor: Michael J. Murdoch, Munsell Color Science Laboratory, Rochester Institute of Technology

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 and director of the Munsell Color Science Laboratory at Rochester Institute of Technology (RIT). He has more than 25 years of experience in color and imaging, including work on film, printing, and OLED displays with Eastman Kodak (Rochester, NY) and LED lighting with Philips Research (Eindhoven, the Netherlands). He leads a research project on color appearance in augmented reality funded by the US National Science Foundation (NSF) and additionally conducts research on displays and temporally dynamic LED lighting. He holds a BS in chemical engineering from