WEBINAR ON FUNDAMENTALS OF DIGITAL IMAGE PROCESSING DURING COVID LOCK DOWN by by K.Vijay Anand , Associate Professor, Department of Electronics and Instrumentation Engineering , R.M.K Engineering College, Tamil Nadu , India

1. Digital Image Processing
DAY 3- 24/6/2020
TODAYS TOPICS:
• Colour image fundamentals
• RGB
• HSI models

2. Main types of digital
image
Colour image (RGB, CMYK)
•An RGB image has 24-bit information (millions of
colours)
•Channels Red, Green and Blue have 256 colours
each.
•For screen images.
•A CMYK image has a 32-bit information
•Channels Cyan, Magenta, Yellow, and Black have
256 colours each.
•For images used in printing offices.
Indexed colour
•8-bit image information. Availability of 256 colours.
•Suits well for coloured drawing graphics, but not
for photographs.

3. Main types of digital image CONT…..
Line-art, bitmap
•An image element consists of 1 bit; 1 = white
and 0 = black.
•Suitable for the presentation of drawings, for
instance, drawing ink works, black and white line
graphics, and texts.
•Requires little saving space due to the lack of
colours, but requires high resolution in order to
show details accurately.
Grayscale image
•The image has 8 bits and 256 tones of grey;
• 1 = black and 255 = white.
•Requires 8 times more saving space than a line-
art image.
•Suitable for presenting black and white

4. Colorimetric
Color Perception involve Hue, Saturation, and Lightness
Hue :Distinguish among colors such as red, green, and
purple.
Saturation :Refer to how color far from gray.white light
mixed with Hue
Lightness: The perceived intensity of a reflecting object.
Brightness :Refer to the perceived intensity of self-luminous.
White “Pure”
color
Grays
Shades
Tones
Black
© 1992–2008 R.C. Gonzalez & R. E. Woods
Artists Terms
Tint: results of adding white pigments
pure pigments
Shade: comes from adding black pigments
to pure pigments
Tone:results of adding both black and white
pigments to pure pigments

5. Color Image Processing
Green
Color Models:
The Newton Color Circle
CyanYellow
BlueRed
Magenta
•The Newton color circle provides a convenient way to perceive
the additive mixing properties of colors.
•The R,G,B and their complementary colors C,M,Y are placed on
the circle in the order of the wavelengths of the corresponding
spectral colors.

6. Digital Image Processing, 3rd ed.
Gonzalez & Woods
www.ImageProcessingPlace.com
Chapter 6
Color Image Processing
• The separation of colors by a prism expose a continuous range
of spectral colors
© 1992–2008 R. C. Gonzalez & R. E. Woods

7. Digital Image Processing, 3rd ed.
Gonzalez & Woods
www.ImageProcessingPlace.com
Chapter 6
Color Image Processing
• A spectral color is composed of a single wavelength
• The helium-neon laser monochromatic light is red (632 nm).
• Most colored objects give off a range of wavelengths and the
characterization of color is much more than the statement of
wavelength.
© 1992–2008 R. C. Gonzalez & R. E. Woods

8. Digital Image Processing, 3rd ed.
Gonzalez & Woods
www.ImageProcessingPlace.com
Chapter 6
Color Image Processing
© 1992–2008 R. C. Gonzalez & R. E. Woods

9. Primary and Secondary colors

10. CIE Chromatic Diagram
Chromatic values depend on dominant
wavelength and saturation and independent
of luminous energy.
Consider a color C, the we can Write C =
XX + YY + ZZ
Normalize Against X+Y+Z
The XYZ space
x = X/(X+Y+Z) y = Y/(X+Y+Z) z =
Z/(X+Y+Z)
We know that x+y+z = 1, and the
luminance information usually in Y (Y
cef.), thus we can recover X,Y,Z
X = Y (x/y) ; Y = Y ; Z = Y(1-x-y)/y
Plotting these parameters
© 1992–2008 R. C. Gonzalez & R. E. Woods

11. XYZ Space

13. cessing
When two color A and B are added together new color C
lies on the line connects both colors.
In the side Figure, B defines the dominant wavelength,
and the ratio AC to BC expressed as a percent of the
excitation purity of A.
The closer A to C the more light A includes.
Complementary colors are those that can be mixed to
produce white light. D and E on the side Figure are
complementary colors.
Nonspectral color are those that can not be defined by
dominant wavelength such as F. Color gamuts or color
ranges is the effect of adding colors together
© 1992–2008 R. C. Gonzalez & R. E. Woods

14. .
Color Image Processing
© 1992–2008 R. C. Gonzalez & R. E. Woods

16. RGB Color Model
The color range (gamut) RGB
model is defined by the CRT’s
phosphor.
C = RR + GG + BB
Let us look at these colors in
XYZ space RGB NTSC
CIE Monitor
R (0.67, 0.33)
G (0.21, 0.71)
(0.73, 0.26) (0.62, 0.34)
(0.27, 0.71) (0.26, 0.59)
B (0.14, 0.08) (0.16, 0.01) (0.15, 0.07)
© 1992–2008 R. C. Gonzalez & R. E. Woods

17. Generating Image of Three Color Cross sectional Colour Plane (127,G,B)

18. Digital Image Processing, 3rd ed.
Gonzalez & Woods
www.ImageProcessingPlace.com
Chapter 6
Color Image Processing
© 1992–2008 R. C. Gonzalez & R. E. Woods

19. CMY Color Model
Cyan, magenta, and blue are the complements of red, green, blue.
CMY is important when dealing with hardcopy that deposit color
pigments onto paper.
 C  1  R
M   1  G
     
 Y  1 B
 R 1  C 
1    
B 1 Y 
G  1G M
© 1992–2008 R. C. Gonzalez & R. E. Woods

21. In various color processing
applications it is possible to
use the corresponding Red,
Green, and Blue channels
© 1992–2008 R. C. Gonzalez & R. E. Woods

23. .

24. Color Coding for
visualization
© 1992–2008 R. C. Gonzalez & R. E. Woods

25. Digital Image Processing
Color Image Processing

26. Colour Image Processing

27. Digital Image Processing.
Color Image Processing
Color Transformation
© 1992–2008 R. C. Gonzalez & R. E. Woods

28. Digital Image Processing, 3rd ed.
Color Image Processing
© 1992–2008 R. C. Gonzalez & R. E. Woods

29. Digital Image Processing
Color Image Processing
© 1992–2008 R. C. Gonzalez & R. E. Woods

30. Digital Image Processing
Color Image Processing
© 1992–2008 R. C. Gonzalez & R. E. Woods

31. Digital Image Processing, 3rd ed.
Color Image Processing
© 1992–2008 R. C. Gonzalez & R. E. Woods

33. Digital Image Processing, 3rd ed.
Color Image Processing
© 1992–2008 R. C. Gonzalez & R. E. Woods

34. Digital Image Processing, 3rd ed.
Color Image Processing
© 1992–2008 R. C. Gonzalez & R. E. Woods

35. © 1992–2008 R. C. Gonzalez & R. E. Woods

36. Digital Image Processing
Color Image Processing
© 1992–2008 R. C. Gonzalez & R. E. Woods

37. Color Image Processing
© 1992–2008 R. C. Gonzalez & R. E. Woods

38. Color Image Processing

39. © 1992–2008 R. C. Gonzalez & R. E. Woods

43. © 1992–2008 R. C. Gonzalez & R. E. Woods

44. © 1992–2008 R. C. Gonzalez & R. E. Woods

45. Color Image Processing