1. Image Enhancement
To process an image so that the result is more suitable than the original image for a specific application.
Spatial domain methods and frequency domain methods.

2. Spatial Domain Methods
Procedures that operate directly on the aggregate of pixels composing an image
A neighborhood about (x,y) is defined by using a square (or rectangular) subimage area centered at (x,y).

3. Image Enhancement in the
Spatial Domain

4. Spatial Domain Methods
When the neighborhood is 1 x 1 then g depends only on the value of f at (x,y) and T becomes a gray-level transformation (or mapping) function:
s=T(r)
r,s: gray levels of f(x,y) and g(x,y) at (x,y)
Point processing techniques (e.g. contrast stretching, thresholding)

5. Image Enhancement in the
Spatial Domain
Contrast Stretching
Thresholding

6. Spatial Domain Methods
Mask processing or filtering: when the values of f in a predefined neighborhood of (x,y) determine the value of g at (x,y).
Through the use of masks (or kernels, templates, or windows, or filters).

7. Enhancement by Point Processing
These are methods based only on the intensity of single pixels.
r denotes the pixel intensity before processing.
s denotes the pixel intensity after processing.

9. Two Different Images-The Same Histogram

14. Histogram Equalisation in Discrete Form

15. Histogram Equalisation

16. Histogram Equalisation

17. Histogram Equalisation

18. Histogram Equalisation

19. Histogram Equalisation

20. Histogram Equalisation

21. Histogram Equalisation

22. Local (Adaptive) Histogram Equalisation

23. Local Histogram Equalisation

24. Local Histogram Equalisation

25. Local Histogram Equalisation

26. Histogram Specification

28. Histogram Specification Summary

29. Histogram Specification

30. Histogram Specification

31. Example of Histogram Specification for Discrete Signals
original intensities
number of pixels
probability
cumulative CM
equalised
intensities
CM x 7
normalised equalised intensities
790
0.19
1.33 1
1023
0.25
0.44
3.08 3 2
850
0.21
0.65
4.55 5
656
0.16
0.81
5.67 6 4
329
0.08
0.89
6.23
245
0.06
0.95
6.65 7
122
0.03
0.98
6.86 81
0.02

32. equalised intensities normalised equalised intensities
Example (cont.)
desired intensities
probability
cumulative CM
equalised intensities
CM x 7
normalised equalised intensities 1 2 3
0.15
1.05 4
0.2
0.35
2.45 5
0.3
0.65
4.55 6
0.85
5.95 7

33. Example (cont.) original intensities equalised intensities (available)1 3 2 5 6 4 7
desired intensities
equalised intensities
(NOT AVAILABLE!!!) 1 2 3 4 5 6 7
equalised intensities (available) 1 3 5 6 7
NEW intensities (available) 3 4 5 6 7