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[Autogenerated] in this clip,
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we're gonna look at RGB light and additive color and the way images are
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constructed with color and all digital images are through channels.
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Channels contain color.
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Now, let's take a look at this image.
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This is the image that we're gonna be using throughout this course.
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This image is of a CG helicopter over a live action plate.
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Now, right now, we're just gonna look at it for its channels.
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Let's go ahead and do that.
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Now I'm gonna hit the R key, which will give us a view of the Red Channel.
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Now the Red Channel is pixels.
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Now we consume all the way in and look at some individual pixels and we
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can see that each pixel is a different level of gray.
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These levels of grey are what construct the channel that is red.
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Now I'm gonna have to green keyboard, shortcut G and switch to green.
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And I'm gonna switch to blue, which is the Beaky.
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And as I switched through these different channels,
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this is what represents the different colors in the image.
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And these three channels are merely containers, containers for the color.
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Let's take a look at our three primary colors red, green and blue.
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Now, these are what we call rgb colors.
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And you can see these being represented down here in the viewer such as red,
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green,
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blue And you can see Green is right now because this is where my cursor was.
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Sampling is 010 Let's take a look at the blue Blue is 001 and we
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can look over here in the red and red is 100 So all three of these
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colors together is what creates white.
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When a pixel is at 111 we get white, so it zoom out.
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Let's find something that looks like a white pixel.
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There we go.
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This little highlight right here.
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Let's sample that and we can see that we're very, very close toe white.
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We're not quite there, but it we have 11 and 110.99110 So that's very close.
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And we can see that we can also go and find a very dark pixel.
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Very, very dark pixel like maybe in this tire here,
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we can see that we're approaching 000 now.
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It's not quite zero black, but it's very, very close.
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Now let's take a look at how we can create some other colors.
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I'm gonna switch over to this example here,
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and I want you to see I have a red circle and we can see
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it's exactly read on the vector scope.
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And we have a green circle now when red and green combined together,
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this is what we call additive.
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Light green and red add together to form yellow,
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and if I click in the center of the yellow,
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you can see my values.
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Air 110 and the color that this makes is yellow or amber.
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Now that is additive.
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It is adding the two colors together.
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It's adding one with one together to create yellow.
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Now let's add in one more primary color, which is blue.
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Now when we add blue to the red, we get magenta 101 Now,
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when we add the blue to the green,
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we get science in Science is 011 and right in the middle,
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where all colors intersect, we get pure white now.
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This is known as additive color space.
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RGB is the color space that we operate in in all digital
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media because RGB is the color of light.
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These are the three primary colors and secondary colors magenta,
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cyan and amber that create what we know as white light.
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Now we can look at science and weaken split white light using a prism,
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and that produces a rainbow,
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which gives us all the different colors that we perceive with their eyes.
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But in order to reconstruct imagery, RGB is the color of light,
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and that's why images are constructed out of these elements.
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And if we pull these elements away from each other,
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we can see that they separate into their three colors.
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But when they combine, we can create all the different colors that exist.
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Now let's come over here and switch back to our primary image.
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We can see that we have a Red Channel, a green channel on a Blue Channel.
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Channels merely exist to represent the captured late of any given image.
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The fun comes when we take those channels and we change them around,
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and we use them to our advantage.
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But what it's really important to remember is that when
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combining channels or rearranging these channels,
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each channel is merely a container pixels that are represented at
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varying degrees of brightness through their numbers.
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Down here, those numbers represent the intensity of each pixel,
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and when combined, when the three values line up in the exact same pixel space,
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they form one of millions, if not trillions of colors that we see.
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