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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 6
• Reading
– Sections 7.1-7.6: Color Image Processing
CSE 166, Spring 2019 4
Electromagnetic spectrum
CSE 166, Spring 2019 5
Separating visible light
CSE 166, Spring 2019 6
Human eye cones
CSE 166, Spring 2019 7
Mixing light
CSE 166, Spring 2019
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.
8
BLUE
GREEN
RED
CYAN
MAGENTA
YELLOW
RGB color model
CSE 166, Spring 2019
RGB coordinates
9
RGB color cube
XYZ color model andchromaticity coordinates
CSE 166, Spring 2019
Not actual colors
locations; just gives an idea
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Color gamuts
CSE 166, Spring 2019
Averageperson
Computermonitor
Printer
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HSI color model:Relationship to RGB color model
CSE 166, Spring 2019
All colors with cyan
hue
RGB color cube rotated such that line joining black and white
(intensity axis) is vertical
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HSI color model
CSE 166, Spring 2019
RGB color cube rotated such that
observer is on intensity axis, beyond white looking towards
black
Shape does not matter, only angle from red13
RGB color cube
HSI intensity axis
HSI color model
CSE 166, Spring 2019
HS-plane is orthogonal to intensity axis
14
CSE 166, Spring 2019
HSI
RGB
CMYK
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Color models
CMY
Intensity slicing
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Grayscale to 2 colors
Intensity slicing
CSE 166, Spring 2019
Grayscale to 2 colors
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Intensity slicing
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Grayscale to 8 colors
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Intensity slicing
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Grayscale to 256 colors
Colorbar
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Intensity to color transformations
CSE 166, Spring 2019
Grayscale input image
RGBoutput image
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Intensity to color transformations
CSE 166, Spring 2019
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 2019
Multiple grayscale
input images
SingleRGB
output image
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Intensity to color transformations
Near infrared (NIR)
Red (R)
NIR,G,B as RGB R,NIR,B as RGB23
Green (G) Blue (B)
Multiple satellite
grayscale input
images
Output RGB imagesCSE 166, Spring 2019
Intensity to color transformations
CSE 166, Spring 2019
SingleRGB
output image
Multiple grayscale input images,
some outside of visible spectrum
Close up
Physical and chemical
processes likely to affect sensor
response
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Full-color image processing
CSE 166, Spring 2019
Spatial filtering: process each channel independently
25
Full-color image processing
CSE 166, Spring 2019
All RGB channels
HSI intensity channel only
Spatial filtering: image smoothing
26
Difference
Full-color image processing
CSE 166, Spring 2019
All RGB channels
HSI intensity channel only
Spatial filtering: image sharpening
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Difference
Full-color image processing
CSE 166, Spring 2019
Histogram equalization: do not process each channel independently
1. RGB to HSI2. Histogram
equalize HSI intensity
3. HSI to RGB
28
4. HSI saturation adjustment
Next Lecture
• Midterm exam review
CSE 166, Spring 2019 29
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