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PROFESSOR: OK.

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Chris can you say that again?

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Was that close to
what you wrote?

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AUDIENCE: No.

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Mine's like five-year-old words.

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PROFESSOR: OK, well tell
us in five-year-old words

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and we'll see if
they're the same.

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AUDIENCE: [INAUDIBLE]
I found that there

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was a lot of green
counts in the green leaf.

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PROFESSOR: OK.

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So there's lots of green
counts in the green leaf.

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Were there lots of red
counts in the green leaf?

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AUDIENCE: There was a
lot, but not as many

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as the green leaves.

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PROFESSOR: Not as many.

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OK.

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Lauren, how does that fit
in with what you said?

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AUDIENCE: That's pretty
much what I said,

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that there were
more counts if, say,

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you're using the red filter,
then there are more red counts.

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PROFESSOR: OK.

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AUDIENCE: But there are
still green and blue counts.

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PROFESSOR: OK.

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So, in other words, when we look
at an object through a filter,

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if that object has a red
color, if we look at the counts

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that we get through
a red filter,

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that's going to be a lot.

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So by looking at these colors,
you should be able to say,

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if I'm looking at a
region that looks blue,

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I would expect that the counts
from the blue filtered image

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are going to be a lot.

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So what I want
everybody to do is

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turn so that you can
look this direction.

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Actually, I think we're going to
put it over on the other table

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so that everybody can see.

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So you guys are going to have
to scoot around this way.

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So here we have--

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I want everybody to
still be able to see--

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but we have three
different light bulbs.

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We have a red light bulb,
we have a green light bulb,

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and we have a blue light bulb.

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And you can see this
indicates that blue is on,

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this indicates that green is on,
this indicates that red is on.

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Now, we are separating out the
photons that are coming in.

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We're separating
them out by energy.

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We're saying all the low energy
photons, all the red photons,

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we're going to collect
behind our red filter.

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But then when we
turn on our image,

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we get not just red,
because a couple of people

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were looking at
yellow regions looking

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at the yellow sunflower.

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Jalen, what did
you find when you

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looked at the yellow sunflower?

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AUDIENCE: When
[INAUDIBLE] it actually

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had the highest, which was
3.96 times [INAUDIBLE]..

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PROFESSOR: OK.

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But what did you find in green?

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AUDIENCE: Green was about
average, and it was 2.74 times

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[INAUDIBLE].

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PROFESSOR: OK, so it's not that
one was overwhelmingly red.

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But if we take red and we
add in a little bit of green

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at the same time--

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so I'm turning on both of
these lights at the same time--

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I can get a color that
looks like yellow.

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Now, Jalen was saying
it wasn't that here

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yellow's turned
all the way down.

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In this case he said
there was a lot of red.

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So let's turn that up.

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And he said there was a little
bit of yellow-- not as much,

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because this is the same--

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but there wasn't as
much green in the image.

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So what we're doing here when
we're putting these three

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images together,
we're adjusting how

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bright each one of those
pixels looks depending

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on how many counts that we get.

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So by adding in
different colors,

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say we turn the red all
the way down, we get green.

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But if we turn red
back up a little bit,

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we get yellow again.

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So by taking these three
colors, red, green, and blue,

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and collecting photons that
fall into those energy ranges--

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remember, each photon
has its own energy--

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those filters let through
a range of energies.

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They don't just let through
one energy, because remember,

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when we looked at red, it
wasn't that it was just

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one thin strip, it was
that whole section of red.

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But by combining
with other colors--

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let's just take red.

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What do you think will
happen if we take red

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and we combine blue with it?

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Did anybody find
any regions that

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had a lot of red and
at least some blue?

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AUDIENCE: Purple.

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PROFESSOR: You think
we'll get purple.

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Did anybody see
any purple regions?

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So here we've got red and blue.

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00:05:00,710 --> 00:05:02,920
Again, if we turn
blue all the way up,

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00:05:02,920 --> 00:05:05,000
we get something that
looks like purple.

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But when we change the
intensity, or we change

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the flux that we receive--

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this is our little
detector, there's

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just a light bulb inside here--

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when we change that value,
we change the color.

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We add in a little bit of green.

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00:05:18,680 --> 00:05:23,483
If we turn them all all the
way up, what color will we get?

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AUDIENCE: White.

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AUDIENCE: Brown.

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PROFESSOR: I heard brown.

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I heard white.

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AUDIENCE: [INAUDIBLE]

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PROFESSOR: It's a
little bit confusing.

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Because when you're
combining colors,

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like if you're painting, it
works kind of the opposite.

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When you add all the colors
together you get black.

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When you're combining
light together,

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if you add red green,
and blue all the way,

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it's kind of as close to
white as we're going to get.

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We turn the green down a little
bit, and that's kind of white.

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So we can rebuild
these different colors

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00:06:06,780 --> 00:06:10,200
by looking at these
different filtered images.

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00:06:10,200 --> 00:06:12,360
So in a way, what
astronomers have to do

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is they have to
break up the light.

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00:06:13,920 --> 00:06:16,530
They have to somehow
record something

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about the energy of the light.

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Because on most detectors, we
just get the number of counts.

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Well here what
we've done is we've

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recorded the energy by saying,
only let the stuff that's red--

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where the photons that have
energy that we see as red--

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pass through here.

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And then we'll combine
that with the green photons

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and the blue photons.

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00:06:35,970 --> 00:06:38,280
And then we adjust
our contrast and bias

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so that we can get a
real representation

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of the actual color.

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Now, in our eyes, we detect all
those photons at the same time.

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There's three
different little kinds

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of cells in the back of
our retina, one of which

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00:06:51,990 --> 00:06:55,710
responds to red, one of which
kind of responds to green,

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and one of which kind
of responds to blue.

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It's not exactly
that, but it's close.

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00:07:00,450 --> 00:07:03,030
So when all three of
those cells respond,

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our brain says, oh,
that looks white.

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When those cells respond
at different levels,

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if we change this up and down,
if the green responder doesn't

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ring, doesn't go off, we see
that as purple because we've

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got red and blue together.

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So what I want you
guys to do now--

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and when we analyze
colors, we're

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going to do it in this way.

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We're going to create
a true color image,

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and then we're going to
get the number of counts.

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Because by looking at the
relative numbers of counts--

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are there more red
than blue, are there

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more blue than green--

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we can find out something
about the color makeup

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of a particular object.