Colour in Images

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Colour in Images By Olga Kubassova olga_at_comp.leeds
.ac.uk (AI21 Lecture 7)
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Roy G. Biv

• I. Experiment of I. Newton, 1672,

Spectrum of colours red, orange, yellow, green,
blue, indigo and into violet.
Prism does not colouring the light! The order of
the colours in the spectrum is consistent! Each
colour has a unique signature identifying its
location in the spectrum!

• II Experiment of I. Newton

Roy G. Biv
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Wavelength of Light

• The signature of colour is the wavelength of
  light.
• Less than 100 years after Newton's discoveries,
  James Clerk Maxwell showed that light was a form
  of electromagnetic radiation. This radiation
  contains radio waves, visible light and X-rays.

Fig The electromagnetic spectrum, which
encompasses the visible region of light, extends
from gamma rays with wave lengths of one
hundredth of a nanometer to radio waves with wave
lengths of one meter or greater.
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The nanometer is a unit of distance in the metric
scale and is abbreviated as nm. 1 nm 10(-9)
m
Red light has a wavelength of 680 nm
Electromagnetic radiation with wavelengths of 410
nm
Fig A wave representation of three different
light hues red, yellow-green and violet, each
with a different wavelength, which represents
the distance between wave crests.
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Light

• We can describe light as electromagnetic waves
  with colour identified by its wavelength or
• as a stream of minute packets of
  energy-photons - which create a pulsating
  electromagnetic disturbance (electron volt,
  abbreviated eV.)

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Objects can be thought of as absorbing all
colours except the colours of their appearance
Colour of the objects
Fig White light composed of all wavelengths of
visible light incident on a pure blue object.
Only blue light is reflected from the surface.
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The Eye and Colour Sensation
Colour is perceived in the retina by 3 sets of
cones which are photoreceptors with sensitivity
to photons whose energy broadly overlaps the
blue, green and red portions of the spectrum.
Colour vision is possible because the sets of
cones differ from each other in their
sensitivity to photon energy.
Figure A cross-sectional representation of the
eye showing light entering through the pupil.
The photosensitive cells, cones and rods, are
located in the retina cones respond to colour
and rods respond to light intensity
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The sensitivity of the cones to light of the same
intensity but different wavelengths
Fig The response to incident light cone R
(pigment R) has a maximum sensitivity in the
orange-red, cone G (pigment G) in the
green-yellow, and cone B (pigment B) in the blue
portions of the visible spectrum. The
sensitivities of the three cones overlap and the
perceived colour is due to the relative response
of the three cones.
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Colour Representation in Imaging
James Clerk Maxwell's Colour Triangle
Fig The colour triangle. The primary colours /
the subtractive colours. Many, but not all
colours can be represented as a mixture of the
three colour lights. The nearer a point is to an
apex, the higher is the proportion of light of
the colour represented by that apex.
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Representing All Colours Commission
Internationale de l'Eclairage (CIE), 1931 (1967)

• The CIE chromaticity diagram showing wavelengths
  in nanometers (nm) and energies in electron volts
  (eV).
• The area enclosed by the curved line and dashed
  segment include all visible colours. The pure
  spectral colours lie along the curved edge.
• The central point W of the diagram is the white
  produced by an equal mixture of the three
  primaries.

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Hue Saturation Intensity

• Hue, H, specifies the dominant pure colour
  perceived by the observer. The sensation of
  colour can be described in terms of hue.
• Saturation, S, specifies the degree to which a
  pure colour has been diluted by white light to
  produce observed colour. The dominant wavelength
  points on the spectral curve are fully saturated
• Intensity, I, is related to the perceived
  brightness of the colour.

Different ways of obtaining metameric beams of
pink light. Each implies mixture with white light
to obtain pink light, A) by orange light, B) by
mixing red with cyan, or C) by mixing red, green,
and violet. To the eye, these metameric colours
would all appear the same
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The HSI Cone
Intensity
White
Hue
Green
Yellow
Red
Cyan
Saturation
Blue
Magenta
Black
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Colour in analogue TV signals

• Colour is stored separately from Luminance to
  retain compatibility with BlackWhite
  televisions.
• Less bandwidth is used to store the chrominance
  (colour) signals than the Luminance (brightness)
  ....
• This is because the human eye is much more
  sensitive to brightness changes than colour
  changes (colour in broadcast television signals
  is a bit of an approximation to true colour).

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Automatic Colour Processing

• Broadcast television signals and compressed
  images (e.g. JPEG) on a computer use humans lack
  of colour perception to compress images without
  loss of perceptual quality.
• i.e. fit it into less memory or radio bandwidth
• Information IS lost however and often such
  signals are not suitable for accurate automatic
  colour analysis.
• Higher quality (and bandwidth) digital cameras
  are now available that preserve colour
  information for automatic processing (at a
  price!)

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Image Processing in Colour

• Image processing operations (such as contrast
  enhancement) may be applied on each channel
  (R,G,B,H,S,I etc) separately or on
  combinations/subsets of channels.
• Intensity invariant representations (e.g. HS)
  are often used to model colour (to normalise out
  lighting), however noise at low intensities is an
  issue.
• Many image processing operations are simply
  carried out on intensity (grey-scale) images.

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Colour Image Processing
It is possible to use colour information with
specific colour orientated methods to understand
images. For example .... Colour Histograms
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Colour Histograms

• Each bin (graph block) represents the number of
  times a pixel within a particular colour range
  has occurred.
• e.g. between 0 and 5 Hue and 10 and 20 saturation
• The wider the range the less bins (and the more
  general the histogram)

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Colour Histograms Application 1Image Comparison

• Two images containing the same objects will have
  roughly similar colour histograms even if the
  spatial arrangement of these objects is
  different.
• Various quantitative measures can be used to
  compare 2 histograms e.g. sum of absolute
  difference, sum of squared difference and
  cross entropy.

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Image Databases

• Image databases can contain large numbers of
  images so searching manually for an image is not
  possible.
• If they are annotated keyword searches can be
  used as in traditional databases.
• Alternatively a query can be a know image and
  images that are similar to this image may be
  retrieved.
• Colour methods (such as colour histogram
  comparison) may be used in this search

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Colour Histograms Application 2Skin
Segmentation
A histogram is calculated from a patch of the
image This is used to classify each pixel in the
complete image(i.e. if frequency in bin relating
to pixel gt threshold classify as skin)
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Introduction to image processing in MatLab

• Online manual for the Image Processing Toolbox
• A digital image is composed of pixels which can
  be thought of as small dots on the screen.
• Each pixel has intensity value, which represent
  the pixel colour
• You can load / save / display/convert image to
  different formats
• MatLab support BMP/ HDF /JPEG /PCX /TIFF/XWB
  image formats

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Some Interesting Facts

• How many colours we actually need to describe an
  object?
• What colour representation can be used for?
• Human observers and colour image quality
• Perceptual colour differences between two colour
  images