Personal insights on color science

Context
In a previous post I talked about the last event in my field I did attend. Now I want to talk about my perception of this domain which is called color science. I'm pretty sure it can be applied to other fields of research as well.

From the first time I joined this community, from article reader, article contributor to reviewer, committee member and session chair my understanding of what is color science has evolved. One important thing is to stay humble, especially with the new comers. I have been one them, it was impressive. Impressive because you meet the people, authors of research articles that are part of the foundation of you work. You can add a person, a voice to written words, it's actually pretty cool.

There aren't thousand concepts to understand/enter the world of color science. Like in every fields it's about observation and trying to explain what's happening. But here it's all about light - its spectral properties - how we perceive this signal - a single light source to an image in the visible spectrum - and how can we develop robust scientific/engineering "stuffs" around it. What I find interesting is to witness what is the new thing coming each year, how a technical improvement can open a door for further applications.

Color trends
Among the research sub-fields presented at CIC this year I want to come back on four of them.

There is the recurrent discussion about color metrics, from a purely mathematical/geometrical approach to a more perception-wise approach trying to add an average human appreciation of the difference between two signals. Having a good metric is always helpful to evaluate your algorithm/experiment. Over the years the metrics are evolving, context is important (from display calibration to color textile differences...).

There is the what I call "purely geometrical approach" discussion where having a signal as vector of n values - for n wavelength -  a group of sensors - basic configuration made of three basis like RGB basis - you want to know the value of this signal once projected on the known basis/sensors. From that you can jump into optimization, addressing various problems such as finding the scene illuminant/white point, study metamerism. It seems obvious but it's not.

There is printing and 3D printing - there I meant color 3D printing. Just think of how to design a color test-chart for such printing system. HDR display is also coming stronger than ever. What is interesting with these two examples is that they both require to know your workflow, they are the "end" of a process chain: you need to understand the acquisition process to do a good reproduction. Understanding the use of the technology is obviously required.

On the last paragraph one can add the understanding of gamut mapping and how you "move" into your color space as something very important. For printers you have multi-inks system changing the shape of the color space available. For high resolution TV and HDR screen the color gamut shape may not change a lot - almost - but the variability of screen size, intensity scale, technology available make it difficult - to be understood as something cool and challenging for me - to offer a comfortable experience to the user among the different platforms.

Now that I'm a bit more in control with the tools/concepts in my field and sub-fields I have the tendency to prefer the projects combining several concepts - like high quality printing and movie post-production - and I always appreciate to hear how the authors are presenting their projects, which story they are telling us.