Topic 5 - Imaging Mapping - II DIGITAL IMAGE PROCESSING Course 3624 Department of Physics and...
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Transcript of Topic 5 - Imaging Mapping - II DIGITAL IMAGE PROCESSING Course 3624 Department of Physics and...
![Page 1: Topic 5 - Imaging Mapping - II DIGITAL IMAGE PROCESSING Course 3624 Department of Physics and Astronomy Professor Bob Warwick.](https://reader037.fdocuments.us/reader037/viewer/2022110211/56649eb75503460f94bc0cc2/html5/thumbnails/1.jpg)
Topic 5 - Imaging Mapping - II
DIGITAL IMAGE PROCESSING
Course 3624
Department of Physics and Astronomy
Professor Bob Warwick
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5.1 The Perception of Colour
• Although the human eye has only a limited ability to discern
shades of grey (~ 2 5), it does much better with colour
gradations (> 2 8)
• Inclusion of colour invariably adds to the visual content of an
image (eg black and white versus colour TV pictures)
• The human perception of colour is a complex subject. It
depends on both physiological and psychological factors. Also
the eye/brain system is highly adaptive
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The Nature of White Light
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Combining colour pigments
Colour Mixing Experiments
Magenta, cyan, yellow, and black are the colours often used in printing
Magenta, cyan, yellow, and black are the colours often used in printing
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5
The Human Eye
The Retina
Fovea
Macula Optic nerve
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Spectral Sensitivity Curves of Rods and Cones
The range of sensitivity is roughly 400 - 650 nm.
There are three types of cone (blue, green, red).
The rods (dashed) primarily give sensitivity in low illumination
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Tri-Stimulus Colour Theory
Any colour can be reproduced by mixing an appropriate set of three “primary colours” – Thomas Young 1802
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A More Complex Model of Human Colour Perception
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Colour Matching Experiments
Choose three “primary” light sources with spectra P1(λ), P2(λ) & P3(λ)
Colour matching involves adjusting the input light levels β1 β2 β3 to match the tristimulus values of the test colour
C(λ) =
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Colour Matching with Monochromatic Primaries
435.8 nm 546.1 nm 700nm
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The CIE 1931 (All Positive) Colour Matching Functions
The corresponding tristimulus values for an arbitrary spectral colour I are:
The CIE XYZ system was designed so that the Y parameter was a measure of brightness ie luminance. Then
x=X/(X+Y+Z) & y=Y/(X+Y+Z) represent "chromaticity" parameters, (since z = 1 - x – y gives no further colour information)
Thus three parameters define an input in the CIE xyY colour space.
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CIE 1931 Chromaticity Diagram
The outer curve boundary represents the track of monochromatic colours in the x,y plane. (Although in practice the colours shown are restricted by the performance of the display devices.)
The gamut of colours that can be generated using monochromatic primaries at 435.8, 546.1 and 700 nm, lie within the triangle. Similarly the xy coordinates of the three phosphors in a display will define the "realizable" colours of the device
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Alternative Colour Specifications
Colour shade (red, green,blue etc..)
Depends on peak λ
Measures the purity of the colour
Degree of dilution by white light
Luminance Hue Saturation (LHS) Colour Space
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Complementary Colours
Author: Richard Alan Peters II
Colours opposite each other on the colour disk are called “complementary”.
CYAN - REDCYAN - RED GREEN - MAGENTAGREEN - MAGENTA BLUE - YELLOWBLUE - YELLOW
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R
B
G
5.2 Pseudo-Colour TechniquesColour displays utilize three different phosphors (RGB) to generate a set of "realizable" colours. These colours occupy the "colour cube" of the device, which can be visualized as a 3-d space.
The Colour Cube has R,G & B axes normalised so that at full intensity R=G=B=1.
Then R=G=B=0 is black R=G=B=1 is full intensity white
R=G=B= 0 1 represents a grayscale (along the leading diagonal)
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Pseudo-Colour ProcessingPseudo-colour processing involves the use of colour to enhanced the display of a single band (monochrome) image. The input grayscale is subdivided into intervals, against which a set of colours are assigned.
If the number of intervals
is small Density Slicing
Colour Assignment
Grey Level ( f )
Yellow
Red
Blue
Black
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The Colour TableMore sophisticated applications of pseudo-colour involve the use of a colour table. The Colour Table represents a specific (and more systematic) mapping from grey level to RGB colour.
For example:
0 63 127 191 255 f
R,G,B
1
0
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Example: Colour Table with 64 levels
A single band image in pseudo-colour.
XMM Image of SNR G21.5-0.9
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5.3 True Colour and False Colour Techniques
In many applications (e.g., remote sensing, astronomy etc..) more than one image is recorded of the same scene using different spectral filters. Up to three such images can be displayed simultaneously with a "three channel" display system.
In this case the possibilities are:
TRUE COLOUR PROCESSING - where the images are recorded through R,G & B filters and are (respectively). displayed on the R, G and B channels of the display system. In many applications (e.g. photography, TV etc..) special care is needed to achieve an acceptable level of colour fidelity.
FALSE COLOUR PROCESSING - where images recorded in three different wavebands are displayed arbitrarily on the R, G and B channels of the display system.
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Implementation of Colour Enhancementvia the device Colour (Look-up) Table
D/A
Image Store
Colour Look-up
Table
D/A
D/A
Video Out
R
G
B
Single Channel System – Pseudo-Colour
Image Store 1
Colour Look-up
TableD/A Video
OutR
G
B
Image Store 2
Colour Look-up
TableD/A Video
Out
Image Store 3
Colour Look-up
TableD/A Video
Out
Three Channel System – True or False Colour
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DISPLAY
I/P CHANNELS
True Colour
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10 micron image
1.2 micron image
2.2 micron image
DISPLAY
I/P CHANNELS
False Colour
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DISPLAY
I/P CHANNELS
Pseudo Colour
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Pseudo Colour Examples
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True, False or Pseudo Colour ?
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Studying Temporal Changes in Remote SensingExample: Panama Canal