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What color is this?

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You’re probably thinking, "it’s red!"

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which, well, it is.

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And what about this?

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Why, it’s green, of course!

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And what video on color would be complete
without an appearance by our old friend blue?

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We’ve been using these three colors to fool
our eyes and brains into thinking that we’re

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looking at a full-color image for over a century.

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We can do this because of how our eyes and
brains perceive color.

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It’s all about ratios, and though it often
seems a little freaky, we can mimic the effect

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of any real color using just these three in
controlled amounts.

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But now that we have the luxury of bringing
the primary colors of light into the real

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world with bright, monochromatic LEDs, we
can get a glimpse into just how wonderfully

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strange our sense of color perception actually
is.

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In this video, we’re going to look at a
series of demonstrations where objects in

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the real world are lit using light from the
digital world.

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What we’ll find is that things can behave
a little… unexpectedly when we play around

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with light.

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None of the footage in this video has been
altered.

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I promise no matter how weird some of this
looks, I’m seeing the same things in person.

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Let’s start with a brief overview of what
it is we’re doing here.

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I’m using these RGB studio lights to provide
illumination.

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I can control the ratio of red, green, and
blue light they produce by adjusting their hue

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and saturation parameters.

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For the most part, we’ll be staying with
a saturation of 100%, and this means we’ll

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be cycling through the 3 primary colors, red,
green, and blue, as well as various shades

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of the three secondary colors that lie between
them, yellow, cyan, and magenta.

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When I need to, I can switch to standard 
phosphor-coated white LEDs

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which provide a reasonable approximation

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of true, full-spectrum lighting.

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Yes, these lights really are G Bee’s knees.

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In RGB mode, the light they produce is trichromatic,
just like our vision, but each individual

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color is monochromatic, meaning it’s comprised
of a single wavelength.

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And this is where the breakdown between the
real and digital world can occur.

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I’ll explain this in a little more detail
shortly, but first let’s move on to a demonstration.

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We’ll be spending much of this video, in
the dark.

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Here we have a kind of disappearing, color-changing
ink.

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This whiteboard, when lit with apparently
yellow light, appears to have some red writing

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on it.

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Well, watch this.

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Now it’s gone.

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But it re-appears, now as a slightly more
orange color, with the presence of some blue light.

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Now watch as before your eyes the ink becomes
a jet black.

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It stays black even as the light grows brighter
and we approach cyan, before the black turns

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to red once more.

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And finally, it’s gone again.

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What’s happening here?

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Well, the ink on this whiteboard is in fact
red.

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Switching to normal white lighting reveals
that.

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The red ink absorbs nearly all of the light
coming from the green and blue LEDs, which

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is why the ink appears black when the scene
is anywhere between blue and green.

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It doesn’t reflect any of that light back
into the camera.

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But in addition to absorbing the green and
blue light, this red happens to be a near-perfect

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match to the red produced by the light’s
red LEDs.

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And that’s why it disappears under red light.

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The white of the whiteboard reflects pretty
much all of the red light back to the camera,

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as do most white objects, but so does the
red ink.

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And so, there’s very little contrast between
the ink and the board, and the ink effectively

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disappears.

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Let’s move on.

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What color is this can of spray paint?

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It’s pretty hard to tell, isn’t it?

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In fact, it’s impossible to tell.

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Right now, this can of spray paint is being
lit solely by the red LEDs, which means it’s

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lit by a monochromatic light source.

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Doing this fundamentally breaks our color
vision because we rely on the mixing of colors

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to determine what it is we’re seeing.

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Under the same red light, let’s look at
some construction paper.

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This packaging says there are 8 colors here.

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Well, what on Earth are they?

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As far as I can tell, these are red, a darker
red, a differently darker red, and uh,

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more red.

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I think there’s black, too, but I’m not
sure.

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With only one wavelength of light available
in this scenario, there’s just no way to

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know what it is you’re seeing.

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Notice how we cannot tell what the colors
are on these Rubik’s Cubes.

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We can see that each color reflects the light
back in different amounts, causing the stickers

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to appear in different brightness levels,
but they’re all just different shades of

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the same red.

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But, with this being a Rubik’s Cube, we
know the colors are white, yellow, orange,

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red, green, and blue.

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We can make some educated guesses into which
stickers are which colors.

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The brightest are probably red, yellow, orange,
and white, as these will reflect most or all

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of the red light back into the camera.

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The darkest are going to be blue and green.

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Now we can be reasonably sure the darkest
of them all is blue, as that’s farthest

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from red, and the next darkest is green.

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But as far as the bright colors?

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That’s really anybody’s guess.

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The brightest is probably white, but then
again there look to be too many that we might

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call white.

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So white and at least one other color look
kinda the same.

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But which colors are they?

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Well, let’s switch the light over to white
and find out.

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Oh, sorry, this one is actually monochromatic
lemme, lemme get that out of here.

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So, we were right about green and blue, but
orange, white, and yellow all appear to be

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the same.

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Red was actually slightly darker, which you
might not have expected given that we were

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using red light.

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This tells us that the hue of this red is
actually not purely red, as it does absorb

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some of the red we were throwing at it.

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And if yellow and orange were reflecting the
same amount of red light back as white, well

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that again goes to show how strange our color
perception is, and why monochromatic light

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breaks it.

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So how do we see in color?

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Well, in our eyes, we don’t just have a
bunch of plain photoreceptors.

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We have some, known as rods, which just detect
brightness, but those of us with typical trichromatic

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vision also have three types of color-sensitive
cells, called cone cells.

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These are pigmented to filter the wavelengths
of light that hit them.

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Now, we often think of these cone cells as
being sensitive to red, green, and blue light.

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Which is broadly true, but their actual stimulation
curves look like this.

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Notice how the medium and long cones, which
correspond to green and red, kinda, overlap

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a lot, but the short cone is way over there.

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Well, where they are along the spectrum doesn’t
actually matter all that much.

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What matters is that they respond differently
to any given color.

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Say we have a yellow-green wavelength right
here.

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Well, for this one color, and this one color
only, the long and medium cones get equal

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stimulation, and the blue cones get negligible
stimulation.

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This unique ratio allows our brains to interpret
this color as yellow-green.

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As we move towards red and head into yellow,
now the medium cone gets progressively less

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stimulated, and the long cone gets more stimulation.

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So, our brains know this color is closer to
red than it is green.

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As we continue moving deeper into true red,
the stimulation from the long cone starts

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to taper off, but the medium cone is tapering
off faster.

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The important thing to remember is that any
color at all along the visible spectrum will

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cause a unique ratio of stimulation between
these three cells, and so our brains know

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what color that is.

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And so, we can easily fool our eyes and brains
into thinking we’re seeing any color at

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all by using just three primary colors.

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We need one of them to be way over here, so
that the long cone gets a fair bit of stimulation,

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but the medium cone doesn’t get all that
much.

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So we’ll use red.

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We also need one to the left of the long-medium
crossover, that way it stimulates the medium

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cone more intensely than the long.

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So we’ll use green.

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And of course, we also need one way over here
that stimulates the short cone a lot, but

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doesn’t really influence the other two.

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So we’ll use blue.

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Now, to make a color like yellow-orange, we
can simply mix red and green together, so

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that there’s a lot of red and a bit of green.

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This mixture causes the same stimulation that
an actual yellow-orange object would.

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Because there’s overlap between the three
cone cells, all real colors just cause a unique

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mix of stimulation between the three of them.

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That includes, by the way, white, which is
all three in close to equal amounts.

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So, if we use three pure colors that allow
us to selectively stimulate the three cells

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with any given ratio, we can artificially
reproduce all visible colors.

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Our eyes simply don’t have a way to know
they’re being fooled.

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But while we can make any color appear by
using just three colors in different ratios,

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that doesn't mean that the world will look
right without the whole spectrum to paint

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the whole picture.

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And unless we have a way to make the cone
cells get stimulated in different ratios,

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we can’t see color at all.

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And with that in mind, let’s move onto some
more demonstrations.

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This scene contains many red objects.

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But, under monochromatic blue light, you’d
never know.

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Watch what happens, though, when I add just
the tiniest amount of red light.

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Suddenly, the red pops into existence.

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This is a pretty trippy effect in person,
because it’s as if someone’s messing with

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the RGB sliders of real life.

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Until we have red light available, red objects
appear, well, grey or black.

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Even with green light, the same thing occurs.

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Notice how with green and blue light together,
we can start to see the yellow and oranges

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of the Rubik’s Cube become distinct from
the blue and green.

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Still, though, the red objects remain completely
dull.

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Pure green light keeps them in the dark, just
like blue.

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Keep in mind that the green light is still
stimulating the long cones a fair bit, but

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without a third, longer wavelength to allow
for comparison between the long and medium

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cones, our brains cannot see red.

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Plus, since the red objects in the scene aren’t
reflecting any of that green light, they stay dull.

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Add just a hint of red, though, and suddenly
the scene explode into color.

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Now, there is red light to be reflected, and
more importantly for our eyes, there is red

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light to be detected and compared with green
and blue.

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Here’s a different kind of color.

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A game boy color.

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Under blue light, this thing looks weird to
say the least.

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Now I’ll add a bit of red and green, alternately.

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Compare the light on my hand to the light
on the game boy, and you’ll see that overall,

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I’m not changing the color in the scene
much at all.

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But the game boy drastically changes.

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This game boy’s color, by the way, is dandelion.

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Which is of course, to our eyes, a mixture
of red and green.

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An important thing to note is that, just like
our eyes, the camera’s Bayer filter (which

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actually separates subpixels into red, green,
and blue elements) doesn’t filter red, green,

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and blue perfectly.

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There’s a lot of overlap.

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And I can show it to you, even with only one
wavelength to see.

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You might assume that if light is a monochromatic
green, then the camera’s blue and red subpixels

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will never become active.

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But this isn’t true.

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If I overexpose the image, you’ll see that
it starts turning white.

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That happens because even though the light
source is monochromatic, the red and blue

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filters will still let some through, so the image
starts to turn white with enough exposure.

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The same thing happens with blue and red.

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However, this doesn’t mean we can start
to tell colors apart.

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We still only have one wavelength illuminating
the scene, which means the ratio of stimulation

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in the camera’s subpixels stays the same.

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The camera’s method of vision is surprisingly
similar to our eye’s.

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Well, as a matter of fact it’s built for
our eyes.

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And even under normal exposure levels, there
is some green slipping in.

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You might expect the image to turn black if
I remove all of the red channel, but in fact

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there’s a faint green image hiding underneath.

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That green is actually helping to define the
ultimate hue of the red we’re seeing on-screen.

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Which brings me to my next demonstration.

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We can have a monochromatic light source of
any color, not just red, green, and blue.

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With RGB lights, I can only produce yellow
light by mixing red and green.

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This then becomes a dichromatic color, and
if I illuminate this scene with it, we can

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actually tell some of the colors apart.

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We can even kinda tell blue from green.

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But, if I break out my yellow traffic light
module (or amber, whatever), this is in fact

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a monochromatic yellow.

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This color looks quite similar to the yellow
I’ve been making by mixing red and green,

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but it’s actually very different.

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So now, even though the green and red subpixels
are both getting stimulation from the yellow

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light, because it’s actually just yellow
they always receive the same relative stimulation

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no matter what’s in the scene.

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Our eyes, and the camera, both see these two
sources of light as essentially the same color,

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but if we use them to illuminate the real
world, and take a look at how they get reflected

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back, we discover they’re actually very
different.

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And that brings us to what makes this whole
ordeal so messy.

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You may have heard of a term called the color
rendering index, or CRI.

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This describes how well an artificial light
source reproduces the color of the objects

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around us.

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Incandescent lights, being a blackbody radiator,
had a perfect CRI, just like the sun, but

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more efficient LED and fluorescent light sources,
indeed practically all light sources that

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aren’t incandescent, don’t emit light
as a perfectly uniform spectrum.

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Now, as we know, one of the most common ways
to mimic white light is to produce red, green,

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and blue light, because, well, if you haven’t
figured that out by now you’ve not been

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paying much attention.

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This works absolutely fantastically for creating
a display device like the one you’re staring

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at now.

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Because it’s providing its own illumination,
it doesn’t need to worry about how the red,

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green, and blue channels interact with the
objects around you.

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It just needs to fool your eyes into thinking
they’re looking at a full-color image.

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And, well, displays are getting better and
better, with incredibly lifelike colors, all

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from just three colors of light.

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Except for that one time Sharp got all weird
with the yellow subpixel which was absolutely

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unnecessary especially since nobody’s encoding
color in an RGB-Y space, but I digress.

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But the problem with using just three colors
of light to illuminate the real world is that

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this rarely looks right.

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Think about that whiteboard earlier.

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The red ink was invisible under red light.

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This meant that it reflected practically all
of the red light back.

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Now, imagine I’m using these lights with
red, green, and blue all working together.

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This looks white to my eyes,

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but when it gets
reflected off of the objects around me, the

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ratio of colors coming back can be way off.

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In the case of the whiteboard, the red looks
way too intense and bright.

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Which makes sense.

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If one third of the light from these lights
is red, and the red ink reflects all of it,

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it’s suddenly freakishly bright because,
well, red is not one third of the color spectrum.

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Under true white light, a much greater percentage
of light gets absorbed, and the red appears

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more dull, like it should.

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As a quick note, this is the one demonstration
where the camera couldn’t quite capture

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what my eyes were seeing.

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The difference in person is much more dramatic.

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The problem here is that the ability to reduce
the real world into three wavelengths of light

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is not reversible.

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If we have a truly white light source, then
all the in-between colors get reflected as

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they truly are.

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Our eyes can see any wavelength of light because
of all that overlap between the cone cells.

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And indeed, cameras can see any wavelength
of light, because their RGB bayer filters

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also have overlap between them.

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And so we can reproduce the stimulation real
objects cause in our eyes with just three

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wavelengths of light, but we cannot expect
those three wavelengths to produce the same

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stimulation ratios that they should when they
hit and get reflected off of real objects

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in the real world.

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This can perhaps best be demonstrated by the
color purple.

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Purple is a rather strange color in general.

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It, along with magenta, are what are called
non-spectral colors.

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If you look on the color spectrum, you’ll
find violet just on the other side of blue,

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but true violet is rather dull, and in fact
we have a hard time seeing it.

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Which is no surprise since it barely registers
with any of our cone cells.

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Purple and magenta are kinda similar to real
violet, but in a sense, these colors exist

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only in our minds.

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That’s pretty wild, when you think about
it.

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Now obviously purple things exist in nature
and we can see them with our eyes, so it’s

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not like the color is imaginary.

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But, it cannot be reproduced with a single
wavelength of light.

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We only see purple and magenta when our eyes
receive blue and red stimulation,

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but little green.

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00:15:50,040 --> 00:15:54,710
Therefore, purple and magenta objects absorb
a fair bit of green light, but reflect both

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red and blue.

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00:15:56,330 --> 00:16:01,310
And luckily, our brains have synthesized this
combination of stimulation into magenta, and

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not the average wavelength between them, as
we do with yellow and cyan.

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Otherwise, it would be another green.

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Anyway, let’s take a look at our old friend
Putt-Putt.

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This particular anthropomorphic automobile
is a rather vibrant shade of purple.

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Now, using the phosphor-coated white LEDs,
he looks pretty normal.

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00:16:19,240 --> 00:16:22,060
But when I switch to the RGB LEDs,

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well not so much.

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00:16:24,130 --> 00:16:26,230
Under green light, he looks pretty dull.

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Which we might expect, given that we can of
course make purple by mixing red and blue

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00:16:30,760 --> 00:16:34,940
pigments, which will together absorb mostly
green wavelengths.

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When we add blue light, well now he just looks
blue.

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All into the cyan range, Putt-Putt looks just
like a blue, and once we hit blue, well now

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he looks kinda like a grey, as his white features
become blue, and his body becomes a slightly

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darker blue.

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But here’s the weirder thing.

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Add red, and now he really looks grey.

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00:16:56,250 --> 00:17:01,760
If I change the angle so you can see his tongue,
yes cars have tongues, duh, his tongue is

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00:17:01,760 --> 00:17:05,280
bright red, but his body still looks grey.

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00:17:05,280 --> 00:17:10,449
And perhaps stranger still, replace the blue
with some green and move into yellow territory

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00:17:10,449 --> 00:17:12,400
and he looks… burgundy?

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00:17:12,400 --> 00:17:14,020
A burnt red?

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00:17:14,060 --> 00:17:17,360
I don’t know exactly what this color is,
but it is not purple.

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00:17:17,360 --> 00:17:22,000
Now, some of this is down to how our brains’
white balance works, as we are comparing his

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00:17:22,000 --> 00:17:26,819
white eyes to his body color, and in fact
if we look in Photoshop we’ll see that what

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00:17:26,819 --> 00:17:29,429
looked grey to us is actually fairly purple.

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00:17:29,429 --> 00:17:32,820
It’s not the right purple, but it is purple.

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00:17:32,820 --> 00:17:35,400
And when you think about it, that makes perfect
sense.

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00:17:35,400 --> 00:17:40,920
Assuming this shade of purple is just a darker
magenta, then if lit with magenta light, his

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00:17:40,920 --> 00:17:46,379
body would appear to be the same hue as his
white features, but at a reduced intensity.

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Without any sort of color contrast, that reduction
in intensity just looks … grey.

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00:17:51,940 --> 00:17:56,920
Grey is simply a darker version of white,
and what is white in this scene, is actually

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00:17:56,920 --> 00:17:58,200
magenta.

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00:17:58,200 --> 00:18:01,500
This also explains why his tongue looks so
vibrant.

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00:18:01,500 --> 00:18:06,049
His tongue is now the only thing actually
changing the relative amounts of color being

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00:18:06,049 --> 00:18:07,690
reflected back.

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00:18:07,690 --> 00:18:12,350
Since it absorbs blue like a good red should,
it’s now able to set itself apart from the

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00:18:12,350 --> 00:18:15,070
magenta mess that is everything else.

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00:18:15,070 --> 00:18:18,740
And of course, we can also explain why he
looks red under yellow light.

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00:18:18,740 --> 00:18:22,370
His body will be absorbing most of the green
coming from the lights, so the only thing

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00:18:22,370 --> 00:18:24,519
it reflects back is red.

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00:18:24,519 --> 00:18:28,659
It looks a little weird because of the fact
that it does absorb some of the red just as

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00:18:28,659 --> 00:18:32,470
it absorbs some blue, so it looks darker than
his tongue.

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00:18:32,470 --> 00:18:36,409
And our brains’ vain attempt to compensate
for the yellow light and assume that’s real

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00:18:36,409 --> 00:18:38,840
white makes it look stranger, still.

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00:18:38,840 --> 00:18:41,289
Now we’re not quite yet done with Putt-Putt.

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00:18:41,289 --> 00:18:45,299
So far, I’ve been showing you how he looks
under various colors of light.

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00:18:45,299 --> 00:18:50,580
But even under apparently white light, comprised
of red, green, and blue, this purple color

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00:18:50,580 --> 00:18:54,700
simply does not get rendered correctly at
all.

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00:18:54,700 --> 00:18:59,720
Notice how differently he looks under normal
white light using the phosphor-coated LEDs,

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00:18:59,720 --> 00:19:03,990
compared to the false white made by the RGB
LEDs working together.

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00:19:03,990 --> 00:19:08,450
Something about the way this purple absorbs
wavelengths in the visible color spectrum

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00:19:08,450 --> 00:19:12,919
simply cannot be reproduced using a trichromatic
RGB light source.

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00:19:12,919 --> 00:19:15,030
At least, not these lights.

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00:19:15,030 --> 00:19:19,659
So keep in mind that even though I can show
you this royal purple on a screen using only

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00:19:19,659 --> 00:19:24,830
some red, some green, and some blue, I can’t
just use those three colors in the real world

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00:19:24,830 --> 00:19:27,110
and expect to achieve the same result.

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00:19:27,110 --> 00:19:31,580
Now, before I leave you, well first of all
that can of paint was yellow, sorry I forgot

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00:19:31,580 --> 00:19:35,320
to answer that earlier, but more importantly
while setting these demos up I think I may

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00:19:35,320 --> 00:19:40,190
have accidentally discovered one of the most
effective ways to understand color blindness.

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00:19:40,190 --> 00:19:44,710
Now, I’ve seen lots of simulated images
online, but they’ve never really clicked

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00:19:44,710 --> 00:19:46,550
with me like this did.

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00:19:46,550 --> 00:19:50,270
The most common type of color blindness is
red-green colorblindness.

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00:19:50,270 --> 00:19:55,389
There are varying degrees of this deficiency
but in general it means that the green / medium

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00:19:55,389 --> 00:19:57,920
cones are either malfunctioning or not present.

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00:19:57,920 --> 00:20:02,999
Now, I have no way to turn down or otherwise
stop the green cones in my eyes from working.

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00:20:03,000 --> 00:20:08,720
But, if I light the room I’m in with dichromatic
magenta light, the effect is somewhat similar.

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00:20:08,720 --> 00:20:11,529
Now, it’s not like this is what a color-blind
person sees.

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00:20:11,529 --> 00:20:16,040
Especially because the entire scene is intensely
colored, and green objects, like this marker,

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00:20:16,040 --> 00:20:18,710
appear very dark, not simply similar to red.

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00:20:18,710 --> 00:20:23,350
But, for the first time, I truly felt like
I could not distinguish red and green all

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00:20:23,350 --> 00:20:24,350
that well.

355
00:20:24,350 --> 00:20:29,139
The snake figure, here, suddenly had its red
and lime green become awfully similar.

356
00:20:29,139 --> 00:20:33,250
Again, this is by no means accurate, look
at how the green stickers on the Rubik’s

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00:20:33,250 --> 00:20:37,429
Cube look black, but it is certainly interesting
to have the color information of the real

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00:20:37,429 --> 00:20:40,700
world become limited in ways I’ve never
experienced.

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00:20:40,700 --> 00:20:42,789
Anyway, that’s it for now, I think.

360
00:20:42,789 --> 00:20:46,630
I didn’t buy these lights assuming I was
going to make a video about how strange RGB

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00:20:46,630 --> 00:20:50,230
lighting is, but playing around with them
led to some interesting places.

362
00:20:50,230 --> 00:20:55,000
And honestly, it’s helped me understand
color vision even better than I did before.

363
00:20:55,000 --> 00:20:58,080
Thanks for watching, and as always a huge
thank you goes out to the people supporting

364
00:20:58,080 --> 00:20:59,370
this channel on Patreon.

365
00:20:59,370 --> 00:21:03,720
Thanks to the support of people like you,
I can make bizarre little detours like these,

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00:21:03,720 --> 00:21:04,990
and I really enjoy it.

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00:21:04,990 --> 00:21:06,320
I hope you do, too.

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00:21:06,320 --> 00:21:10,360
If you’d like to join these people in supporting
my work, you can check out the link in the description.

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00:21:10,360 --> 00:21:12,880
Thanks for your consideration, and I'll see you next time!

370
00:21:13,920 --> 00:21:16,920
♫ trichromatically smooth jazz ♫

371
00:21:18,820 --> 00:21:19,320
Hey!

372
00:21:19,320 --> 00:21:20,160
It’s me!

373
00:21:20,160 --> 00:21:21,480
But from the future!

374
00:21:22,060 --> 00:21:22,560
Woah.

375
00:21:23,380 --> 00:21:27,340
So many of you probably know this but if you
didn’t, I have a second channel where I

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00:21:27,340 --> 00:21:31,889
sometimes upload rather random things, they
tend to be kind of rambly, and I wanted to

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00:21:31,889 --> 00:21:36,659
let you know that following this video I want
to have a more relaxed discussion about some

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00:21:36,659 --> 00:21:41,779
of the subtle differences between using true
white lighting and RGB white lighting.

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00:21:41,779 --> 00:21:45,350
So if you want to check that out, there’s
gonna be a link in the description as well

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00:21:45,350 --> 00:21:47,700
as a card on the end screen.

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00:21:47,700 --> 00:21:51,740
For now, I hope you’re enjoying this rather
groovy looking Rubik’s Cube.

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00:21:51,740 --> 00:21:53,440
It's pretty groovy looking.

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00:21:54,180 --> 00:21:54,900
Groovy.