I am currently in the third year of the PhD program at the Munsell Color Science Laboratory at RIT in Rochester, NY. Studying color science has fundamentally shifted the way I look around me and how–in the words of James Turrell–I see myself see. I have become an expert MATLAB user through the program, as I have used software development to study our visual system

Currently, I am developing my dissertation topic. Broadly, I am interested in understanding how our visual system uses the color of the illumination to form perceptions of object colors. It is my goal to develop a unique experimental apparatus that will allow me to probe this phenomenon (often referred to as color constancy) in novel ways.

Find out more about my past research below.

Image Copyright James Turrell

I am currently funded through my position at MCSL as the lab’s Color Metrology Specialist. My main task in this position is to learn as much as I can about our color measurement instruments and lab equipment from our lab guru, Dave Wyble, so that this information can be passed on to future generations of students after Dave retires. So, essentially, I am being paid to become an expert in color measurement!

In addition to providing lab support to the department, I have also used this position to create a GitHub repository for our department. This repository is allowing us to share important MATLAB code that is used to do color calculations in research and to run some of our color measurement instruments. Collaborating on code with other students has allowed me to become more confident with object-oriented programming and performance-conscious programming.

In the above figure, does one set of six patches look more uniform in hue than the other? A past research project of mine looked at our perception of hue and hue-linear color spaces. This research resulted in a paper that will be published in the Journal of Perceptual Imaging, so if you are interested, I would recommend reading the paper there. In brief, I looked at whether Gaussian-shaped spectra of the same peak wavelength but varying bandwidths could be used as loci of constant hue (figure below left). I used those hue loci derive a color space definition using non-linear optimization in MATLAB (figure bottom right). I then ran a psychophysical experiment to compare how well different color spaces predict perceived hue (figure above).

The 2019-2020 school year also saw me complete a research project funded by HunterLab. Their Agera device that is capable of taking both spectrophotometric measurements and camera images without moving the sample. This combination allows for the measurement of inhomogeneous samples, which usually is not recommended with spectrophotometers. I helped HunterLab develop a robust colorimetric image processing pipeline. I also tested models for how the spectral reflectances of separate regions combine into a single spectrophotometer measurement. Significantly, I developed a process by which the spatial sampling function of the spectrophotometer could be derived, using a combination of images and spectrophotometric measurements.

Image copyright HunterLab.

The effect of illumination on color perception is an important question for warm-CCT “Night Modes” that are built into many electronic devices. Because the color of each pixel (under a normal white point) is defined simply by RGB and not by full reflectance spectra, it is impossible to say what the “true” color of that pixel should be under a warm-CCT white point. For a class project in 2019, I explored how different algorithms to shift the white point of a display generate slightly different results (above images).