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Color Image Processing
Image Processing
CSE 166
Lecture 9
Announcements
• Assignment 3 is due today, 11:59 PM
• Midterm exam is on May 4
• Reading
– Sections 7.1-7.6: Color Image Processing
CSE 166, Spring 2020 5
Electromagnetic spectrum
CSE 166, Spring 2020 6
Separating visible light
CSE 166, Spring 2020 7
Human eye cones
CSE 166, Spring 2020 8
Mixing light
CSE 166, Spring 2020
Light
Pigment
Primary and secondary colors are swapped
Note that green, cyan, and blue are not accurate colors in the book. More
accurate colors below.
9
BLUE
GREEN
RED
CYAN
MAGENTA
YELLOW
RGB color model
CSE 166, Spring 2020
RGB coordinates
10
RGB color cube
XYZ color model andchromaticity coordinates
CSE 166, Spring 2020
Not actual colors
locations; just gives an idea
11
Color gamuts
CSE 166, Spring 2020
Averageperson
Computermonitor
Printer
12
HSI color model:Relationship to RGB color model
CSE 166, Spring 2020
All colors with cyan
hue
RGB color cube rotated such that line joining black and white
(intensity axis) is vertical
13
HSI color model
CSE 166, Spring 2020
RGB color cube rotated such that
observer is on intensity axis, beyond white looking towards
black
Shape does not matter, only angle from red14
RGB color cube
HSI intensity axis
HSI color model
CSE 166, Spring 2020
HS-plane is orthogonal to intensity axis
15
CSE 166, Spring 2020
HSI
RGB
CMYK
16
Color models
CMY
Pseudocolor image processing
• Intensity slicing
• Intensity to color transformations
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Intensity slicing
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Grayscale to 2 colors
Intensity slicing
CSE 166, Spring 2020
Grayscale to 2 colors
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Intensity slicing
CSE 166, Spring 2020
Grayscale to 8 colors
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Intensity slicing
CSE 166, Spring 2020
Grayscale to 256 colors
Colorbar
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Intensity to color transformations
CSE 166, Spring 2020
Grayscale input image
RGBoutput image
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Intensity to color transformations
CSE 166, Spring 2020
X-ray grayscale input image
Misses explosive
RGB output images
Without explosive
With explosive
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Intensity to color transformations
CSE 166, Spring 2020
Multiple grayscale
input images
SingleRGB
output image
24
CSE 166, Spring 2020
Intensity to color transformations
Near infrared (NIR)
Red (R)
NIR,G,B as RGB R,NIR,B as RGB25
Green (G) Blue (B)
Multiple satellite
grayscale input
images
Output RGB images
Intensity to color transformations
CSE 166, Spring 2020
SingleRGB
output image
Multiple grayscale input images,
some outside of visible spectrum
Close up
Physical and chemical
processes likely to affect sensor
response
26
Full-color image processing
• Two approaches
– Process each channel independently
– Process color vector space
CSE 166, Spring 2020 27
Full-color image processing
CSE 166, Spring 2020
Spatial filtering: process each channel independently
28
Full-color image processing
CSE 166, Spring 2020
All RGB channels
HSI intensity channel only
Spatial filtering: image smoothing
29
Difference
Full-color image processing
CSE 166, Spring 2020
All RGB channels
HSI intensity channel only
Spatial filtering: image sharpening
30
Difference
Full-color image processing
CSE 166, Spring 2020
Histogram equalization: do not process each channel independently
1. RGB to HSI2. Histogram
equalize HSI intensity channel
3. HSI to RGB31
4. HSI saturation adjustment
Next Lecture
• Midterm exam review
CSE 166, Spring 2020 32
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