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It's a bit strange to me, because how does a colorspace "predict" anything? But maybe I get it. Is it that since a lab colorspace has lightness and opponent co

It's a bit strange to me, because how does a colorspace "predict" anything? But maybe I get it. Is it that since a lab colorspace has lightness and opponent color coordinates, a lab colorspace, for example, "predicts lightness well" when a small increase in the L coordinate leads to a small increase in the perceived lightness of the resultant color?

chrismorgan 6y ago
The gradients offer good examples. Take the blue–white gradient: that’s about saying “what happens if we take a certain blue, and lighten it?” Expressed otherwise: “given ‘blue’, what do people think ‘light blue’ is?” It’s predicting light blue, based on the shape baked into the colour model. sRGB blending says “blue channel’s already full, let’s increase the red and green channels”. That’s tolerable, but not great. Most people will look at it and be very subtly discontent, though they probably can’t quite place their finger on what’s wrong with it. It’s just a little too indigo. CIELAB does a terrible job of this particular prediction. People will tend to agree that its guess at light blue is actually a light purple. IPT, Oklab and ICtCp have been modelled to know that, in order to lighten a blue, you actually have to add a little more green than red (increase the green channel more than the red channel), because that’s just how our eyes and brains work, how we perceive colours. Or the blue–yellow gradient: it’s asking “what colour is half-way between blue and yellow?” sRGB thinks a mid-grey is, and CIELAB thinks mauve is: these two are quite clearly wrong. The interesting ones are that IPT and ICtCp think a sort of teal is, while Oklab thinks it’s a bit paler and not quite so green. These are the predictions that have been designed into the colour space. Who’s more correct? I dunno, actually. They’re both pleasant to look at.
- rodarmor 6y ago
  This is a great explanation! Thank you, it makes perfect sense now.
deleted 6y ago
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chrismorgan 6y ago

The gradients offer good examples. Take the blue–white gradient: that’s about saying “what happens if we take a certain blue, and lighten it?” Expressed otherwise: “given ‘blue’, what do people think ‘light blue’ is?” It’s predicting light blue, based on the shape baked into the colour model. sRGB blending says “blue channel’s already full, let’s increase the red and green channels”. That’s tolerable, but not great. Most people will look at it and be very subtly discontent, though they probably can’t quite place their finger on what’s wrong with it. It’s just a little too indigo. CIELAB does a terrible job of this particular prediction. People will tend to agree that its guess at light blue is actually a light purple. IPT, Oklab and ICtCp have been modelled to know that, in order to lighten a blue, you actually have to add a little more green than red (increase the green channel more than the red channel), because that’s just how our eyes and brains work, how we perceive colours. Or the blue–yellow gradient: it’s asking “what colour is half-way between blue and yellow?” sRGB thinks a mid-grey is, and CIELAB thinks mauve is: these two are quite clearly wrong. The interesting ones are that IPT and ICtCp think a sort of teal is, while Oklab thinks it’s a bit paler and not quite so green. These are the predictions that have been designed into the colour space. Who’s more correct? I dunno, actually. They’re both pleasant to look at.

rodarmor 6y ago
This is a great explanation! Thank you, it makes perfect sense now.

deleted 6y ago

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