I recall reading in a magazine a while ago about how functional tetrachromats (individuals able to process color information in four independent channels) were extremely rare among humans but nonetheless still existed. This makes me curious about what specific effects tetrachromacy has on individual color perception.
Related to the question of "Do different people see the same color in different ways?" is the inverted spectrum problem, which asks whether two healthy people with the same ability to distinguish colors, actually experience those colors in different ways. In other words, is my blue your red? This is a question of philosophy, and you can read more about it here: https://en.wikipedia.org/wiki/Inverted_spectrum
Fun fact: sinospheric culture often use same character to represent both green and blue interchangeably. The modern Chinese character of blue (lan) only referred to a plant that produces blue dye in ancient China. During ancient China, (qing) are used to describe both green and blue, even sometimes black. eg qing shan(green mountain), qing tian (blue sky) qing si (black hair). Interestingly, in modern Japanese, (ao, the same character as qing in Chinese) is used to refer to blue. Also, many Chinese dialects use qing to refer to blue.
It seems like this doesn't support Chinese character...sad
I'd like to learn about illusions like the scintillating grid illusion where different areas of the image light up depending on where your eyes are focused. I wonder how much of this has to do with color or just the contrast between the colors in the image.
Color determines how an image appeals to people a lot - currently, photo editing tools have presets that people could use to give an image a certain feel to it. However, I feel like presets don't work super well because every image starts out with different qualities (color, lighting, etc.). For example, a "white" filter that turns an image into an aesthetic bright white-ish looking photo doesn't necessarily work on some photos. I wonder if with color qualities, taking into account of how an image originally looks, we can come up with an algorithm that turns every possible different image into the same looking image in terms of color.