Colour - PowerPoint PPT Presentation

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Colour

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... patches: difficult to distinguish colours in the yellow-blue direction ... want here and hardly anyone would want to put in the effort to see what it was I ... – PowerPoint PPT presentation

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Title: Colour


1
Colour
  • CPSC 533C
  • February 3, 2003
  • Rod McFarland

2
Ware, Chapter 4
  • The science of colour vision
  • Colour measurement systems and standards
  • Opponent process theory
  • Applications

3
The science of colour vision
  • Receptors and trichromacy theory

Red ?
Green ?
Blue ?
4
Colour measurement systems and standards
  • Any colour can be matched using a combination of
    three primaries.
  • The primaries are not necessarily red, green, and
    blue. Any three different colours can be used.
    The range of colours that can be produced from a
    given set of primaries is the gamut.

5
Colour standards
  • CIE (Commission Internationale dÉclairage)
  • Primaries chosen for mathematical properties do
    not actually correspond to colours. These
    virtual colours X, Y, and Z are called
    tristimulus values.
  • Y is the same as luminance

6
CIE Chromaticity
  • Chromaticity is derived from tristimulus values
  • Since xyz1, just use x, y values and luminance
    (Y).
  • Chromaticity diagram

7
Uniform Colour Space - CIEluv
  • Uniform colour space a representation where
    equal distances in space correspond to equal
    distances in perception
  • Useful for
  • Specification of colour tolerances
  • Color coding (maximum distinction)
  • Pseudocolour sequences to represent ordered data
    values
  • CIE XYZ color space is not uniform
  • CIEluv is a transformation of the chromaticity
    diagram

8
  • CIEluv does not solve all problems
  • Contrast effects
  • Small colour patches difficult to distinguish
    colours in the yellow-blue direction

9
Opponent process theory
  • Black-white (luminance), red-green, and
    blue-yellow opponents
  • Has basis in biology and culture
  • Should use opponent colours for coding data

10
Properties of Colour Channels
  • Isoluminant / Equiluminous patterns a colour
    pattern whose components do not differ in
    luminance
  • Red-green and yellow-blue channels carry only
    about 1/3 of the detail carried by black-white.

11
Yellow Text on a Blue Background
  • Is fairly easy to read unless the text is
    isoluminant with the background colour. As the
    luminance of the background becomes the same as
    the luminance of the text, it is very difficult
    to make out what the text says. So much so, that
    at this point I can write just about anything I
    want here and hardly anyone would want to put in
    the effort to see what it was I had written.

12
Other isoluminance effects
  • Stereoscopic depth is not detectable with
    isoluminant colours
  • Isoluminance in animation makes it appear to be
    slower than the same animation in black-and-white
  • Shape and form are best shown using luminance

13
Colour appearance
  • Contrast
  • Saturation
  • Brown

low
high
14
Applications
  • Colour selection interfaces
  • Colour naming
  • Natural Colour System (NCS) e.g. 0030-G80Y20
  • Blackness 00, intensity 30, green 80, yellow 20
  • Pantone, Munsell standard colour chips

15
Applications
  • Colour for labelling (nominal information
    encoding)
  • Distinctness
  • A rapidly distinguished colour lies outside the
    convex polygon defined by the other colours in
    CIE space

16
Applications
  • Colour for labelling (2)
  • Unique hues universally recognized hues (red,
    green, blue, yellow, black, white) should be used
  • Contrast with background border around objects

17
Applications
  • Colour for labelling (3)
  • Colour blindness majority of colour-blind people
    cannot distinguish red-green, but most people can
    distinguish blue-yellow
  • Number only 5-10 codes easily distinguished

18
Applications
  • Colour for labelling (4)
  • Size
  • Colour-coded objects should not be very small
    (about ½ degree minimum size).
  • Smaller objects should be more highly saturated,
    large colour-coded regions should have low
    saturation. Text highlighting should be
    high-luminance, low-saturation.
  • Conventions
  • Common usage of colours, e.g. redstop,
    greenready, bluecold

19
Applications
  • Colour for labelling (5)
  • Wares 12 recommended colours (in order of
    preference)

20
Applications
  • Pseudocolour sequences for mapping
  • Pseudocolouring is the practice of assigning
    colour to map values that do not represent colour
  • Medical imaging
  • Astronomical images
  • Mapping nonvisible spectrum information to the
    visible spectrum (astronomy, infrared images)
  • Gray scale best for showing surface shape
  • Colour best for classification

21
Applications
  • Colour for mapping (2)
  • For orderable sequences, black-white, red-green,
    blue-yellow, or saturation (dull-vivid) sequence
    can be used.
  • For detailed data, the sequence should be based
    mainly on luminance. For low letail, chromatic or
    saturation sequences can be used.
  • Uniform colour spaces can be used to create
    colour sequences where equal perceptual steps
    correspond to equal metric steps.
  • Where it is important to be able to read off
    values from a colour map, a sequence that cycles
    through many colours is preferable.

22
Applications
  • Colour for mapping (3)
  • A spiral through colour space (cycling through
    several colours while continuously increasing in
    luminance) is often a good choice.
  • Hue 0, 50,250, 45, 95
  • Luminance 0, 25, 50 225

23
Applications
  • Colour for mapping (4)
  • Perception even if the sequence is smooth,
    people tend to see discrete colours, potentially
    miscategorizing data.
  • My personal division into blue, green, yellow,
    orange, red, purple very nonlinear

24
Applications
  • Colour for mapping (5)
  • Using colour for 3-D information mapping
  • Difficult to read accurately
  • May be used to identify regions
  • Satellite images regions of invisible spectrum
    mapped to red, green, blue channels

25
Applications
  • Colour for multidimensional discrete data
  • 5-D plot using (x, y) position, red, green, blue
  • Possible to identify clusters
  • Ambiguous is a point low-red or high-green?
  • Other methods needed to analyze clusters once
    identified

26
Rogowitz et al. How Not to Lie with Visualization
  • Visual representation of data affects the
    perceived structure of the data.

27
Enhancing data interpretation using Colour
  • Perceptual impact of a colour is not predictable
    from the red/green/blue components of the colour
  • Mapping different aspects of colour to different
    data is not intuitively decodable by users.
  • Default colour maps rainbow
  • Perceptual nonlinearity
  • False contours
  • Yellow attracts attention

28
Guiding colour map selection
  • Constrain the set of colour maps available to the
    user based on
  • Data type
  • Data spatial frequency
  • Visualization task
  • Other design choices made by user

29
Representing Structure
  • Nominal data
  • Object should be distinguishably different but
    not perceptually ordered
  • Ordinal data
  • Distinguishable with perceptual ordering
  • Interval data
  • Equal steps in data correspond to equal steps in
    perceived magnitude
  • Ratio data
  • Zero point distinguishable in colour sequence

30
Structure
  • Magnitude of a variable at every spatial position
  • Use luminance (gray scale) or saturation

31
Spatial Frequency
high spatial frequency
low
saturation-based
luminance-based
32
Segmentation
  • Low frequency more segmentation steps can be
    used

33
Highlighting
Luminance-based map can be highlighted using hue
variations. The highlighted regions have the same
luminance value as the rest of the map.
34
PRAVDA
  • Perceptual Rule-Based Architecture for
    Visualizing Data Accurately
  • Part of IBMs Visualization Data Explorer
    (http//www.research.ibm.com/dx/)
  • Provides choices for colour maps based on spatial
    frequency, data type, and user-selected goal
    isomorphic (structure-preserving), segmentation,
    highlighting

35
PRAVDA
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