Figures from Gonzalez and Woods, Digital Image Processing, Second Edition, 2002. - PowerPoint PPT Presentation

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Figures from Gonzalez and Woods, Digital Image Processing, Second Edition, 2002.

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Lecture 17 Figures from Gonzalez and Woods, Digital Image Processing, Second Edition, 2002. Psuedocolor Processing Produce RGB image (usually) from gray levels. – PowerPoint PPT presentation

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Title: Figures from Gonzalez and Woods, Digital Image Processing, Second Edition, 2002.


1
Lecture 17
  • Figures from Gonzalez and Woods, Digital Image
    Processing, Second Edition, 2002.

2
Psuedocolor Processing
  • Produce RGB image (usually) from gray levels.
  • Also possible to transform a number of monochrome
    images.

3
Chapter 6 Color Image Processing
4
Chapter 6 Color Image Processing
5
Typical Transformations
  • Sinusiodal functions with differing start points

6
Chapter 6 Color Image Processing
7
Chapter 6 Color Image Processing
8
Chapter 1 Introduction
9
Chapter 1 Introduction
10
Chapter 6 Color Image Processing
11
Chapter 6 Color Image Processing
12
Color Transformation
13
Chapter 6 Color Image Processing
14
Color Transformations (2)
  • Also possible in
  • CMYK components
  • HSI components

15
Chapter 6 Color Image Processing
16
Modify through intensity
17
Chapter 6 Color Image Processing
18
The Wheel of Hues
  • Notice how complementary colors are opposite one
    another

19
Chapter 6 Color Image Processing
20
Effect of Complementary Transformation
  • Notice difference in RGB vs. HSI model

21
Chapter 6 Color Image Processing
22
Color Slicing
23
Chapter 6 Color Image Processing
24
Chapter 6 Color Image Processing
25
Chapter 6 Color Image Processing
26
Histogram Processing
  • Done to intensity component. Should not be done
    to RGB components.
  • Next figure
  • Histogram equalization to intensity
  • Then increased saturation

27
Chapter 6 Color Image Processing
28
Smoothing and Sharpening
  • Smoothing filters (like averaging or low pass)
  • Or sharpening (like Laplacian or high pass)
  • Are usually done on R,G,B components
  • Or on intensitywith slightly different results

29
Chapter 6 Color Image Processing
30
Chapter 6 Color Image Processing
31
Chapter 6 Color Image Processing
32
Chapter 6 Color Image Processing
33
Color Segmentation
  • As done in HSI space
  • Color represented by hue image
  • Saturation used to perform masking
  • Intensity contains no color information and not
    used much for segmentation

34
Chapter 6 Color Image Processing
35
Color Segmentation
  • Done with distances in RGB space
  • Either Euclidean or maximum are easy to do
  • In fact, looking at this example, my thought was,
    oh, thats what you want!

36
Chapter 6 Color Image Processing
37
Chapter 6 Color Image Processing
38
Color Noise
  • Handled naturally in RGB mode.
  • Standard color models make sense

39
Chapter 6 Color Image Processing
40
Chapter 6 Color Image Processing
41
Chapter 6 Color Image Processing
42
Chapter 6 Color Image Processing
43
Chapter 6 Color Image Processing
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