Warmup: What is your favorite color?

Transcription

1 Warmup: What is your favorite color?

2 Perception and Color Lecture 23 November 22, 2015

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4 Light Comes from a source Travels in a straight line Hits things and bounces is absorbed (turned into something else)

5 Light Particle model Comes in packets (photons) Each contains a wavelength (over-simplification warning!)

6 Some implications 1. Sensing counts photons in a place 2. You don t know where they came from

7 Measuring Light (simplified) Amount (intensity) number of photons Properties kinds of those photons

8 It s raining photons

9 Measure the rate in different places

10 Kinds of buckets Chemical Semiconductor Biological

11 Strategy 1 (chemical, eletronic) 1. Open the lid for a period of time 2. Close the lid 3. Measure how much is in each bucket 4. Empty the buckets and repeat

12 Sensitivity big buckets catch more photons catch enough to count (otherwise noisy) Resolution big buckets take up more space less spatial measurements

13 Strategy 2 (biological) 1. Photon cracks molecule in half 2. Molecule gives off charge when cracked 3. Molecule gets repaired (put back together) 4. Repeat Output is a pulse train faster = higher rate

14 Varieties of Photo-receptors Retinal Cells Have photo-pigments (rhodopsin) Two kinds: Rods Cones

15 120 million rods 5-6 million cones 1 5 Wandell, Foundations of Vision (left) David R. Williams, Univ. of Rochester (right)

16 E. B. Goldstein Sensation and Perception (Adapted from Lindsay & Norman, 1977)

17 Ware

18 Rods Big Sensitive Spread out All one type Night vision Peripheral motion Cones Small Less-sensitive Concentrated in places 3 different types Normal vision

19 Without Color: Brightness How do we encode amount of light? In a way that makes sense perceptually

20 How many different levels? Side by Side can you distinguish next to each other? 1% differences (in ideal case) 1.01 x =100 (x approx 460) Note: 1.01, , , 99, 100 In practice 2^8 = 256 is more than enough

21 Non-Linear 1.01, , , 99, steps OK if the right 256 steps Gamma Correction Convert levels to display amounts

22 Display Calibration Tune so it looks right Setting Gamma white = 100% black = 0% 50% grey = 50% (black&white checks)

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24 (warning resampling messes things up)

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26 Why is color so complicated?

27 Different Ways we get at Color Physics of Color Sensing Color Representing / Reproducing Color Specifying Color

28 Different Ways we get at Color Physics of Color Why a vector space for colors? Sensing Color Why is 3 numbers enough? Representing / Reproducing Color Which 3 numbers? Specifying Color

29 The physics view of color

30 Frequency vs. Wavelength

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32 Physics of Color Spectral Colors all one kind of photon Distributions of colors Black White Other

33 Physicists: Spectral Distribution From Stone s A Field Guide to Digital Color

34 To a physicist: A Color is A distribution over the spectrum F(w) (w in wavelengths) White Neon laser (red) Red-looking color

35 Colors of Materials What colors of light are reflected/absorbed If you shine white light on it, what bounces off All kinds of other issues

36 Perception How do we sense color?

37 Measuring Light (simplified) Amount (intensity) number of photons Properties kinds of those photons

38 Measure the rate in different places

39 Measure the rate in different places

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41 Once converted to something else, Color information is lost

42 Filter so different buckets get different colors

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44 Strategies Put filters over the buckets Give up spatial resolution to get color resolution Design buckets to only count certain colors Stack the buckets on top of each other and make the bottoms leak some colors Use a prism to split the light Use Fancy Optics and Materials

45 Different Responses to Wavelengths Red Bucket Green Bucket

46 Different Responses to Wavelengths Green Photons Count Green Bucket Red Photons Don t

47 Different Responses to Wavelengths Green Photons Count Green Bucket Red Photons Don t Other Greens Count

48 Metamers Green Bucket Different Colors Same Measurement

49 A Bi-Chromat Two receptor types 2 measurements Did you see 2 red, 2 blue 4 green 1 yellow, 2 blue

50 Real Animals Some mono-chromats Dichromats (many mammals) Tri-Chromats (humans, dinosaurs) Tetrachromats (some birds, some humans) Pentachromats (pigeons, ducks)

51 Human Vision 3 kinds of cones, Long, Medium, Short Rod M L S Short Wavelength Higher Energy Long Wavelength Lower Energy

52 What does this mean? A color sensation is 3 measurements response to L response to M response to S Each spectral color gives a different ratio

53 Faking out a human You could make any color sensation with 3 lights If you had the right colors

54 Imaginary color systems No color can excite just M or L cones Rod M L S Short Wavelength Higher Energy Long Wavelength Lower Energy

55 Real Color Systems 3 primaries (RGB) Rod M L S Short Wavelength Higher Energy Long Wavelength Lower Energy

56 Representing Color as 3 Numbers

57 3 Numbers good enough? For physics? No! All human perception? 3 numbers, imaginary primaries In Practice?

58 Computer Graphics: RGB Cube based on three primary colors Green What (most) monitors use

59 Gamuts Visible colors (grey) versus colors supported by the display (triangle) Gamut: Colors that can be created using the three display primaries

60 Gamut Analysis "CIExy1931 Rec 2020 and Rec 709" by CIExy1931.svg: Sakuramboderivative work: GrandDrake (talk) - CIExy1931.svg. Licensed under CC BY-SA 3.0 via Wikimedia Commons

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62 Practical Concerns Violet? Deep Red? not sensitive enough Extra primaries? expensive! Special for white/black

63 Some other color systems

64 Printing Red, Green, Blue = light colors additive primaries Inks subtract light subtractive primaries

65 Color Blending Monitors & Light Physical Pigments CMYK

66 CMY and K White Green = Magenta (red-blue) White Blue = Yellow (red-green) White Red = Cyan (blue-green) Printing black is important, so have a special fourth ink color

67 Problems with RGB (or CMY) (and some alphabet soup to replace it) Doesn t cover all sensations - XYZ Inconsistent (primaries matter) - srgb Not perceptually uniform LAB Inconvenient for users - HSV

68 Luminance / Brightness Roughly the sum of the 3 channels: L = R + G + B (ok,.299r +.587G +.114B) Y = X + Y + Z

69 Luminance as an axis Y X

70 Equi-luminant Y X

71 Easier to analyze color space Make one axis be lightness L ~~ R+G+B let s us say equally bright Other two directions are color Define so measurements are meaningful Equal distance = equally distant colors

72 CIELAB L: Lightness AB: Hue/saturation plane based on opponent responses Euclidean distance is meaningful!

73 Why do we care? LAB lets us talk about color differences! Are two colors distinguishable? Are a series of colors equally spaced? Important for analysis.

74 Artist-friendly color systems

75 How do people talk about color?

76 Depends on who Physicists (distributions) Vision scientists (cone responses) Computer graphicists (device primaries) Color theorists (perceptually uniform spaces) Normal folks

77 Nameable Colors Language effects vision! Lots of uniformity around world Nameability adds distinctness

78 Describing Color Luminance: How light something is Saturation: How colorful something is Hue: What color something is

79 From Gretag-Macbeth Artists Think in terms of lightness/hue/saturation Munsell Look-up Tables

80 HSV/HSL

81 HSV

82 It s a cone (or double cone) No light (black) no hue no saturation No saturation (grey) no hue white at fully bright