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Digital Media

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!)

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Digital Media

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  1. Digital Media Lecture 6: Color Part 1 Georgia Gwinnett College School of Science and Technology Dr. Jim Rowan

  2. Refer to Supplemental text: What is color anyway?   How do we model color?   Color Theory

  3. 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…

  4. Light http://en.wikipedia.org/wiki/Electromagnetic_spectrum

  5. 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

  6. Spectral Power Distribution

  7. Color • We need to reproduce it electronically and manipulate it digitally • So… we need a way to model color as numbers

  8. 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

  9. 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

  10. 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

  11. 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? ==>

  12. 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

  13. Color Gamut http://en.wikipedia.org/wiki/Gamut

  14. 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)

  15. RGB • Full onred • (255,0,0) • Full ongreen • (0,255,0) • Noblue • (0,0,0) • What color do you get? • HMMMMMmmmm…

  16. RGB • It’s yellow! • Weird but true! • Full onred • (255,0,0) • Full ongreen • (0,255,0) • Noblue • (0,0,0)

  17. Mixing Colors • Mixing light.. • is an additive process • monitors emit light • Mixing paint… • is a subtractive process • paint absorbs light

  18. 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

  19. 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 • 24 bits => 224 => 16,777,216 choices

  20. Color at 16 bit Color Depth16 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?

  21. …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

  22. 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)

  23. 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

  24. 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

  25. Indexed (indirect) colorwith 256 colors in palate • Even though it allows for a closer-to-real-life image • natural images will have more than 256 different colors… • What to do about this? • use the nearest color • optical mixing... dithering

  26. Nearest color results in posterization http://en.wikipedia.org/wiki/Posterization

  27. Dithering (optical mixing)Black and White to shades of Gray http://www.flickr.com/photos/edward_on_flickr/4790092474/sizes/l/in/photostream/

  28. Dithering (optical mixing) http://en.wikipedia.org/wiki/Dither

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