The Appearance Layer of Color Perception

Eighth in a series of blog entries about color theory with live help from the ColorTheory (Step 8) .  First_post,  Prev_post, Next_post

In the last two posts, we discussed how the eye perceives color, first through its red, green, and blue cone response, then through its black-white, red-greeen, and yellow-blue opponent responses. But that isn’t the end of the story.

In this post, we’ll discuss three dimensions of color appearance- hue, luminance or value, and colorfulness or saturation. These dimensions were first carefully worked out by Munsell, but we will look at the latest model, the CIE Color Appearance Model 2002 (CIECAM02, or simply CAM02).

For the RGB model, the appearance variables are the well-known HSV- Hue, Saturation, and Value. But these are only rough approximations to the real variables, chosen to be easy to compute.

For better models, we go to the CIECAM02 model. It defines variables JCH: J for Lightness which corresponds to Value, C for Chroma which the amount of color (where the Saturation is the fraction of color), and H for hue (but measured differently from the HSV hue)

Red and Unique Green

Equal Lightness

Equal Chroma

We’ll demonstrate the differences by using two fully-saturated colors in the RGB space- a pure red, and a pure unique green, both with 100% Saturation and 100% Value. So in RGB, these colors differ only by hue. But they differ radically in both the perceived Lightness and the perceived Chroma (colorfulness).

The appearance of Lightness clearly varies by how white or black a color is, but it is more than just the grayness of the color. It also varies by the hue of the color- green-cyan is inherently lighter than red. In the figures above, we have to darken the green to match the lightness of the red.

Chroma, the appearance of colorfulness,also varies by the amount of gray: pink has less chroma than red. But it also varies by color- only this time, red is more colorful than green-cyan. In the figures above, we have to add gray to the red to reduce its chroma to that of the green-cyan.

The color wheel assumed that we map the most colorful to the rim of the wheel. But the CIECAM02 model is also trying to model the non-uniformity of how we perceive color, and this is not compatible with the circular geometry of the wheels we have considered to date. So to properly display the CIECAM02 model, we need to change that.

In the new wheel, the outer boundary is mapped to the true chroma of the color. So we see that Red, Green, Blue, and Magenta have high chromas (>90), Yellow has less chroma (80), and Cyan and Orange have the lowest (<65).

I’ll leave this with one more demonstration that to me at least shows the importance of understanding the more accurate appearance models.

HSV Contrasts

When I look at this wheel, I am very aware of the “blocks” of colors and their apparent borders. There is an optical illusion where each block, although of uniform color, appear darker at its outer border where it abuts a lighter shade, and lighter at its inner border where it abuts a darker shade. In this wheel, we also see a similar phenomenon on the side borders as well, seemingly saying something about how colors behave when they abut other hurs.

Contrast under Constant Lightness

And here, by removing the contrasts due to lightness/luma, for me the illusions of borders in the blocks mostly disappears. Which means that most of the illusion seen before was almost entirely due to lightness contrasts, and not color contrasts.

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