Digital Media
Lecture 6: Color Part 1
Georgia Gwinnett College
School of Science and Technology
Dr. Jim Rowan
Refer to Supplemental text:
What is color
anyway? How do we model
color? Color Theory
Color
Is a mess (humans are a mess!)
 It’s a subjective sensation PRODUCED
in the brain
 Color differs for light and paint/ink
 Print is different than viewing monitors

– Monitors EMIT light
– Print ABSORBS the colors EXCEPT the color
that you see
– A ball that is painted green and viewed in a
room that is lit by blue light will look black...
• Why?
• HMMMMMmmmm…
Light
http://en.wikipedia.org/wiki/El
omagnetic_spectrum
Light

Visible light from the sun is a mix of
different wavelengths of light at
different intensities

Most light is composed of different
frequencies at different intensities
– Spectral Power Distribution
Spectral Power Distribution
Color

We need to reproduce it electronically
and manipulate it digitally

So… we need a way to model color as
numbers
But first… Bird eye trivia

Eagles have 600,000 cones per square
mm of retina, humans have 150,000

The chestral (a bird) has cones that can
see UV light (we don’t)

Owls “see” with their ears
– they have flaps that are offset in front of
the ear openings to detect vertical
positioning
One model of color:
roughly based on the eye

Human eye has:
– Rods (night vision, B&W)
– Cones (3 kinds, one for red, one for blue
and one for green) ==> RGB

tri-stimulus theory:
– the theory that states any color can
be completely specified with just 3
values
RGB model

Color is captured as 3 numbers
– one for red
– one for green
– one for blue

Color is displayed on a monitor by
generating 3 different colors
– one for red
– one for green
– one for blue
RGB

3 colored things with the number
representing the intensity

Results in the display of most
(Not All!) of the visible colors

Why not all colors? ==>
Most (not all) colors?

The 3 different cones in the eye are
cross connected in very complex ways
– The firing of one receptor can inhibit or
accentuate the firing of another
The model we use assumes (wrongly)
that each receptor is strictly sensing R
or G or B
 ==> RGB cannot completely reproduce
the visual stimulus

Color Gamut
http://en.wikipedia.org/wiki/Gamut
RGB

Pure red
– (255,0,0)

Pure green
– (0,255,0)

Pure blue
– (0,0,255)

White/Black/Gray?
–
–
–
–
R=G=B
(25,25,25)
(150,150,150)
(200, 200, 200)
RGB

Full on red
– (255,0,0)

Full on green
– (0,255,0)

No blue
– (0,0,0)
What color do you get?
 HMMMMMmmmm…

RGB
It’s yellow!
 Weird but true!


Full on red
– (255,0,0)

Full on green
– (0,255,0)

No blue
– (0,0,0)
Mixing Colors

Mixing light..
– is an additive process
– monitors emit light

Mixing paint…
– is a subtractive process
– paint absorbs light
How many colors?
Different cultures have different ideas
about when 2 colors differ
 People individually differ in their ability
to distinguish between two colors


A range of 0-255
– can be encoded in 1 byte (8 bits)

24 bit RGB results in 16.8 million
possible colors
– 2**24 = 16,777,216
Color Depth
Usually expressed in bits
 One byte for each of the RGB

– => 24 bits

Back to binary...
–
–
–
–
1
2
4
8
bit => 21 => 2 choices
bits => 22 => 4 choices
bits => 24 => 16 choices
bits => 28 => 256 choices
– 24 bits => 224 => 16,777,216 choices
Color at 16 bit Color Depth
16 bits to represent a color

RGB with 24 bit color depth
– 24 bits => 3 bytes
– 3 bytes, 3 colors => one byte per color

RGB with 16 bit color depth
–
–
–
–
–
16 bits => 2 bytes
2 bytes, 3 colors...
16/3 = 5 bits with one left over...
HMMMmmmm...
What to do?
…16 bit color depth
16/3 = 5 bits with one bit left over...
 What to do with the extra bit?
 Go back to human perception

– Humans do not discriminate Red or Blue as
well as they do Green
– Evolutionary roots?
• Our environment is green
• Lots of green to discriminate

Assign 5 bits to R & B, and 6 bits to G
– allows twice as many greens as blues and
reds
Why would you want more than
16.8 million?
24 bit depth is plenty for human vision...
 48 and 64 bit color are WAY more than
needed for human vision...
 If you scan at 48 bit color there is a lot
of information buried in the image that
we cannot see BUT...
 This information can be used by the
program to make extremely fine
distinctions during image manipulation
(edge finding for example)

– (Failed rocket engine example)
Indexed (indirect) color
vs.
8 bit (direct) color

8 bit (direct) color defines only 256
colors
– red through blue
– 256 choices, whether they are
used or not

Indexed color allows 256 different
colors
– colors that actually exist in the
image
Indexed color
vs.
8 bit direct color

But images in nature have a narrower
range of colors... a palate
– 8 bit direct color only allows 256 choices

With indirect color you can store 256
different colors that are actually found
in the image
– results in an image that more closely
mimics scene
Indexed (indirect) color
with 256 colors in palate

Even though it allows for a closer-toreal-life image
– natural images will have more than 256
different colors…

What to do about this?
– use the nearest color
– optical mixing... dithering
Nearest color results in
posterization
http://en.wikipedia.org/wiki/Posterization
Dithering
(optical mixing)
Black and White to shades of Gray
http://www.flickr.com/photos/edward_on_flickr/4790092474/sizes/l/in/photostream/
Dithering
(optical mixing)
http://en.wikipedia.org/wiki/Dither