32
1 Vladimir Botchko [email protected] Lecture 5. Color Image Lecture 5. Color Image Processing Processing Lappeenranta University of Technology (Finland)

Vladimir Botchko [email protected]

  • Upload
    nessa

  • View
    58

  • Download
    0

Embed Size (px)

DESCRIPTION

Lappeenranta University of Technology (Finland). Lecture 5. Color Image Processing. Vladimir Botchko [email protected]. Color Image Processing. Fundamentals Color models Pseudocolor image processing Full color image processing Color transformations Smoothing and Sharpening - PowerPoint PPT Presentation

Citation preview

Page 1: Vladimir Botchko  botchko@lut.fi

1

Vladimir Botchko [email protected]

Lecture 5. Color Image ProcessingLecture 5. Color Image Processing

Lappeenranta University of Technology (Finland)

Page 2: Vladimir Botchko  botchko@lut.fi

2

Color Image ProcessingColor Image Processing

Fundamentals Color models Pseudocolor image processing Full color image processing Color transformations Smoothing and Sharpening Color segmentation Noise in color images Color image compression Multispectral image processing

Page 3: Vladimir Botchko  botchko@lut.fi

3

Fundamentals

Colors in the visible range of wavelengths (upper left), mixtures of light (additive primaries) (upper right) and color bars used in analysis.

Page 4: Vladimir Botchko  botchko@lut.fi

4

Color models

Relative color gamuts of a dipslay and a printer in XYZ chromaticity coordinate system (right).

Left - XYZ color space.

Page 5: Vladimir Botchko  botchko@lut.fi

5

Color Image ProcessingColor Image Processing

Fundamentals Color models Pseudocolor image processing Full color image processing Color transformations Smoothing and Sharpening Color segmentation Noise in color images Color image compression Multispectral image processing

Page 6: Vladimir Botchko  botchko@lut.fi

6

Color models

http://cvision.ucsd.edu/index.htm

Page 7: Vladimir Botchko  botchko@lut.fi

7

Color models

RGB system, HSI (or HSV) system (right) (I-intensity, V value)

Page 8: Vladimir Botchko  botchko@lut.fi

8

Color models

Three match curves. RGB system (CIE 1931)(left), XYZ system (CIE 1931)(right)

Page 9: Vladimir Botchko  botchko@lut.fi

9

Color models

RGB space. The right image is a rotated left image (for correspondence: BL is black, W is white).

Page 10: Vladimir Botchko  botchko@lut.fi

10

Hue, saturation, intensity system

Y aR cG dBr g b

r g bW PW S

r g b

UV|||W|||

arccos[( / ) ( / ) ( / ) ]

min( , , )

/

26 1 3 1 3 1 3

1 3

2 2 2 1 2

Page 11: Vladimir Botchko  botchko@lut.fi

11

Color models

Chromaticity

r R R G Bg G R G Bb B R G B

UV|W|/ ( )/ ( )/ ( )

g

r0r g b 1b r b 1

w( / , / )1 31 3

Page 12: Vladimir Botchko  botchko@lut.fi

12

Color models

Multitriangle representation (left) Luminance, chromaticity (right)

Page 13: Vladimir Botchko  botchko@lut.fi

13

Color models

Karhunen-Loev system

Page 14: Vladimir Botchko  botchko@lut.fi

14

Color Image ProcessingColor Image Processing

Fundamentals Color models Pseudocolor image processing Full color image processing Color transformations Smoothing and Sharpening Color segmentation Noise in color images Color image compression Multispectral image processing

Page 15: Vladimir Botchko  botchko@lut.fi

15

Pseudocoloring

Myocardial perfusion study. Left is a heart attack (blue region increased), right is normal.

Page 16: Vladimir Botchko  botchko@lut.fi

16

Pseudocoloring. X-rays.

a

Page 17: Vladimir Botchko  botchko@lut.fi

17

Pseudocoloring Right – three images: elevation relief (upper left), the color coded

magnetic field (higher values are yellowish) (upper right), the composition of first two. Left – underpainting revealed through color dipslay (Prof. L. MacDonald, Derby University,GB).

Page 18: Vladimir Botchko  botchko@lut.fi

18

Thematic classification of six-band satellite imagery using a minimum distance classifier

Page 19: Vladimir Botchko  botchko@lut.fi

19

Color Image ProcessingColor Image Processing

Fundamentals Color models Pseudocolor image processing Full color image processing Color transformations Smoothing and Sharpening Color segmentation Noise in color images Color image compression Multispectral image processing

Page 20: Vladimir Botchko  botchko@lut.fi

20

Painting Restoration. A Queen house , London. The part of painting was copied from another painting (upper right) and

used for restoration of the lost painting part.

Page 21: Vladimir Botchko  botchko@lut.fi

21

Color Image ProcessingColor Image Processing

Fundamentals Color models Pseudocolor image processing Full color image processing Color transformations Smoothing and Sharpening Color segmentation Noise in color images Color image compression Multispectral image processing

Page 22: Vladimir Botchko  botchko@lut.fi

22

Color segmentation

Image segmentation based on color feature: burnt forest area, forest fire, dead forest (brown).

Page 23: Vladimir Botchko  botchko@lut.fi

23

Color Image ProcessingColor Image Processing

Fundamentals Color models Pseudocolor image processing Full color image processing Color transformations Smoothing and Sharpening Color segmentation Noise in color images Color image compression Multispectral image processing

Page 24: Vladimir Botchko  botchko@lut.fi

24

Color image compression.

Original color image (upper left), compressed image (upper right), error histogram in compression (the error is a delta E – the smallest color noticible difference) and error image (large error values are white).

Page 25: Vladimir Botchko  botchko@lut.fi

25

Color Image ProcessingColor Image Processing

Fundamentals Color models Pseudocolor image processing Full color image processing Color transformations Smoothing and Sharpening Color segmentation Noise in color images Color image compression Multispectral image processing

Page 26: Vladimir Botchko  botchko@lut.fi

26

Using a ratio image to enhance road detail (two upper is a multispectral image components)

The third image (lower) is the dividend of the first two

Page 27: Vladimir Botchko  botchko@lut.fi

27

Color analysis. Color similarity

Brick Ceramic tiles Wooden pieces Car parts

Page 28: Vladimir Botchko  botchko@lut.fi

28

Color analysis. The Munsell Book of Color contains a set of color patches

http://www.it.lut.fi/research/color/demonstration/demonstration.html

Page 29: Vladimir Botchko  botchko@lut.fi

29

Color analysis. Metameric spectra. Color is the same at one illumination (left patches) and different at another

illumination (right patches).

Page 30: Vladimir Botchko  botchko@lut.fi

30

Page 31: Vladimir Botchko  botchko@lut.fi

31

Statistical Analysis of Natural ImagesUpper curve is mean, lower curve is standard deviation

Page 32: Vladimir Botchko  botchko@lut.fi

32

http://www.techexpo.com/WWW/opto-knowledge/ for previous picture site.http://stargate.jpl.nasa.gov/lctf/ for this picture site.