1. CIS 595 Image Fundamentals
Dr. Rolf Lakaemper

2. Parts of these slides base on the textbook Digital Image Processing
Fundamentals
Parts of these slides base on the textbook
Digital Image Processing
by Gonzales/Woods
Chapters 1 / 2

3. basic concepts about digital images
Fundamentals
These slides show
basic concepts about digital images

4. Fundamentals
In the beginning…
we’ll have a look at the human eye

5. Fundamentals

6. consists of cones and rods
Fundamentals
We are mostly interested in the retina:
consists of cones and rods
Cones
color receptors
About 7 million, primarily in the retina’s central portion
for image details
Rods
Sensitive to illumination, not involved in color vision
About 130 million, all over the retina
General, overall view

7. Distribution of cones and rods:
Fundamentals
Distribution of cones and rods:

8. Fundamentals
The human eye is sensible to electromagnetic waves in the ‘visible spectrum’ :

9. Fundamentals
The human eye is sensible to electromagnetic waves in the ‘visible spectrum’ , which is around a wavelength of
m = mm

10. Maps our 3D reality to a 2 dimensional image !
Fundamentals
The human eye
Is able to perceive electromagnetic waves in a certain spectrum
Is able to distinguish between wavelengths in this spectrum (colors)
Has a higher density of receptors in the center
Maps our 3D reality to a 2 dimensional image !

11. maps our continous (?) reality to a (spatially) DISCRETE 2D image
Fundamentals
…or more precise:
maps our continous (?) reality to a (spatially) DISCRETE 2D image

12. Some topics we have to deal with: Sharpness Brightness
Fundamentals
Some topics we have to deal with:
Sharpness
Brightness
Processing of perceived visual information

13. The eye is able to deal with sharpness in different distances
Fundamentals
Sharpness
The eye is able to deal with sharpness in different distances

14. The eye is able to adapt to different ranges of brightness
Fundamentals
Brightness
The eye is able to adapt to different ranges of brightness

15. Processing of perceived information: optical illusions
Fundamentals
Processing of perceived information: optical illusions

16. Fundamentals
optical illusions:
Digital Image Processing does NOT (primarily) deal with cognitive aspects of the perceived image !

17. Fundamentals
What is an image ?

18. Fundamentals
The retinal model is mathematically hard to handle (e.g. neighborhood ?)

19. Easier: 2D array of cells, modelling the cones/rods
Fundamentals
Easier: 2D array of cells, modelling the cones/rods
Each cell contains a numerical value (e.g. between 0-255)

20. The position of each cell defines the position of the receptor
Fundamentals
The position of each cell defines the position of the receptor
The numerical value of the cell represents the illumination received by the receptor 5 7 1 12 4 … … …

21. With this model, we can create GRAYVALUE images
Fundamentals
With this model, we can create GRAYVALUE images
Value = 0: BLACK (no illumination / energy)
Value = 255: White (max. illumination / energy)

22. A 2D grayvalue - image is a 2D -> 1D function,
Fundamentals
A 2D grayvalue - image is a 2D -> 1D function,
v = f(x,y)

23. As we have a function, we can apply operators to this function, e.g.
Fundamentals
As we have a function, we can apply operators to this function, e.g.
H(f(x,y)) = f(x,y) / 2
Operator
Image (= function !)

24. H(f(x,y)) = f(x,y) / 2 Fundamentals 6 8 2 3 4 1 12 200 20 10 6 100 103 4 1 12
200 20 10 6
100 10 5

25. Remember: the value of the cells is the illumination (or brightness)
Fundamentals
Remember: the value of the cells is the illumination (or brightness) 6 8 2 3 4 1 12
200 20 10 6
100 10 5

26. Fundamentals
As we have a function, we can apply operators to this function…
…but why should we ?
some motivation for (digital) image processing

27. Transmission of images
Fundamentals
Transmission of images

28. Fundamentals
Image Enhancement

29. Image Analysis / Recognition
Fundamentals
Image Analysis / Recognition

30. Image Acquisition and Representation
Fundamentals
The mandatory steps:
Image Acquisition and Representation

31. Fundamentals
Acquisition

32. Fundamentals
Acquisition

33. Fundamentals
Acquisition

34. Typical sensor for images: CCD Array (Charge Couple Devices)
Fundamentals
Typical sensor for images:
CCD Array (Charge Couple Devices)
Use in digital cameras
Typical resolution 1024 x 768 (webcam)

35. Fundamentals
CCD

36. Fundamentals
CCD

37. Fundamentals
CCD: million pixels !

38. Fundamentals
Representation
The Braun Tube

39. Fundamentals
Representation
Black/White and Color

40. Color Representation: Red / Green / Blue
Fundamentals
Color Representation: Red / Green / Blue
Model for
Color-tube
Note: RGB is not the
ONLY color-model, in fact
its use is quiet restricted.
More about that later.

41. Color images can be represented by
Fundamentals
Color images can be represented by
3D Arrays (e.g. 320 x 240 x 3)

42. But for the time being we’ll handle 2D grayvalue images
Fundamentals
But for the time being we’ll handle 2D grayvalue images

43. Digital vs. Analogue Images
Fundamentals
Digital vs. Analogue Images
Analogue:
Function v = f(x,y): v,x,y are REAL
Digital:
Function v = f(x,y): v,x,y are INTEGER

44. Stepping down from REALity to INTEGER coordinates x,y: Sampling
Fundamentals
Stepping down from REALity to INTEGER coordinates x,y: Sampling

45. Stepping down from REALity to INTEGER grayvalues v : Quantization
Fundamentals
Stepping down from REALity to INTEGER grayvalues v : Quantization

46. Sampling and Quantization
Fundamentals
Sampling
and
Quantization

47. MATLAB demonstrations of sampling and quantization effects
Fundamentals
MATLAB demonstrations of sampling and quantization effects