Digital Media
Dr. Jim Rowan
ITEC 2110
Color
COLOR
• Is a mess
• It’s a subjective sensation PRODUCED in the
brain
• Color differs for light and paint/ink
• Printing is different than viewing a monitor
– a monitor EMITS light of a specific wavelength (or a
combination of them)
– print is like paint... it absorbs all the colors EXCEPT
the color that you see which is reflected by the paint
– a ball that is painted yellow and is viewed in a room
that is lit by a light that is completely blue will look
black... Why?
Light
• Is electromagnetic radiation (just like
microwaves and radio signals... just
different wavelengths)
• Visible light has a wavelength that is
between 400 and 700 nanoMeters
• A nanoMeter is 1 billionth of a meter...
– HINT: It’s a very short wave
http://en.wikipedia.org
/wiki/Electromagnetic_
spectrum
http://en.wikipedia.org/wiki/Electromagnetic_spectrum
Light
• Visible light is a mix of different
wavelengths of light at different
intensities
• The sun has one Spectral Power
Distribution, fluorescent light another, a
camera flash another and an LED light
another
Color
• To reproduce it electronically or
manipulate it digitally we need a way to
model color.
• i.e. we need a way to convert a
subjective sensation to a reproducible
physical phenomenon
A model of color:
roughly based on the eye
• 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
• Color is specified by 3 numbers
– one for red
– one for green
– one for blue
• Color is displayed on a monitor by 3 different
colored things
– one for red
– one for green
– one for blue
The 3 colored things
• Phosphor for a CRT and Flat panel displays
(aka SED or surface conductor electron
emitter display)
• Pockets of fluorescent gas for Plasma
• a bunch of other stuff too...
• All of them have the ability to adjust the
intensity of each of the three things resulting
in the display of most of the visible colors
http://en.wikipedia.org/wiki/Computer_display
RGB...
Good but not all visible colors
• In truth, the 3 different cones in the eye
are cross connected in very complex
ways
• This keeps the model, which assumes
(wrongly) that each is strictly sensing R
or G or B, from being able to completely
reproduce the visual stimulus
RGB
• Pure red
– (100%, 0%, 0%)
– (255,0,0)
• Pure green
– (0%, 100%, ,0%)
– (0,255,0)
• Pure blue
– (0%, 0%, 100%)
– (0,0,255)
Mixing the Color of Light
• Is an additive process
– monitors emit light
• Is not like mixing paint which 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
• With the range of 0-255 (which can be
encoded in one byte) for each of the
Red, Green and Blue there are 16.8
million possibilities
Color Depth
• Usually expressed in bits
• One byte for each of the RGB => 24 bits
• Back to binary...
–
–
–
–
1 bit => 21 => 2 choices
2 bits => 22 => 4 choices
4 bits => 24 => 16 choices
8 bits => 28 => 256 choices
Color and Grey
• RGB (0, 0, 0) is black
• RGB (255, 255, 255) is white
• When R = G = B you get grey
– RGB (25, 25, 25) is dark grey
– RGB (200, 200, 200) is light grey
Color at 16 bit Color Depth
• RGB at 24 bits
– 24 bits => 3 bytes
– 3 bytes, 3 colors => one byte per color
• RGB at 16 bits
–
–
–
–
–
16 bits => 2 bytes
2 bytes, 3 colors...
16/3 = 5 bits with one left over...
HMMMmmmm...
What to do?
16 bit color
• 16/3 = 5 bits with one left over...
• What to do with the extra bit?
• Go back to human perception
– Humans do not discriminate Blue as well as they
do Green vision
– Evolutionary roots?
• Lots of blue light in daylight
• Lots of green to discriminate
• Assign 5 bits to R & B, and 6 bits to G
– allows twice as many greens as blues
Why more than 16.8 million?
• 24 bits is plenty for human vision...
• 30 and 48 bits 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 than we can
distinguish 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)
Why worry about color depth?
• One reason: file size
• Any reduction in color depth has a 3-fold
effect on the final image size
• A 100X100 RGB image
– at 24 bit color => 30,000 bytes uncompressed
– at 16 bit color => 20,000 bytes uncompressed
– 1 byte => 1/3 reduction of size
Why is too big bad?
• It wastes valuable computer resources
– hard drive disk space
– vram space
– data transit time
• Sure, computers are really fast
and big now BUT...
• Consider Video...
internet
main
memory
monitor
VRAM
hard drive
Indexed color
• We’ve seen this before... the color table
• Used by a number of file formats
– tiff, png, bmp, gif,
• Use a table (color palete) to store colors
• Use a map of logical colors to reference
the color map
Indexed color vs. 8 bit color
• 8 bit color defines only 256 colors
• Indexed color allows 256 different colors
• What’s the difference?
– 8 bit defines 256 colors---whether they are
used or not
– Indexed color allows 256 different colors
that exist in the image
Indexed color vs. 8 bit color
• 8 bit direct color... an example
– suppose...
•
•
•
•
Red gets 3 bits ==> 000, 001, 010, 011... 111 ==> 8 values
Green gets 3 bits ==> 000, 001, 010, 011... 111 ==> 8 values
Blue gets 2 bits ==> 00, 01, 10, 11 ==> 4 values
total different colors ==> 8 x 8 x 4 = 256 different colors
• But images in nature have a narrower range of
colors... a palete
• With indirect color you can store 256 different
colors that are actually found in the image
– results in an image that more closely mimics the image
Indexed color
• Even though it allows for a closer-toreal-life image, some colors must be
modified
• How to do this?
– use the nearest color
– optical mixing... dithering
Nearest color
• Loss of some detail
• Distorted color
• Generates artifacts
– Banding or posterization
Optical mixing: Dithering
• Dithering uses a group of colors to
approximate the desired color
• Works well for high resolution images
• Works poorly for low resolution images
• See figure 6.8, p169 for dithering effects
Questions?