Digital image processing operations can be either point or group. This presentation explains both operations (point and group) and shows how convolution works by a numerical example. Ahmed Fawzy Gad ahmed.fawzy@ci.menofia.edu.eg Information Technology Department Faculty of Computers and Information (FCI) Menoufia University Egypt Find me on: AFCIT http://www.afcit.xyz YouTube https://www.youtube.com/channel/UCuewOYbBXH5gwhfOrQOZOdw Google Plus https://plus.google.com/u/0/+AhmedGadIT SlideShare https://www.slideshare.net/AhmedGadFCIT LinkedIn https://www.linkedin.com/in/ahmedfgad/ ResearchGate https://www.researchgate.net/profile/Ahmed_Gad13 Academia https://www.academia.edu/ Google Scholar https://scholar.google.com.eg/citations?user=r07tjocAAAAJ&hl=en Mendelay https://www.mendeley.com/profiles/ahmed-gad12/ ORCID https://orcid.org/0000-0003-1978-8574 StackOverFlow http://stackoverflow.com/users/5426539/ahmed-gad Twitter https://twitter.com/ahmedfgad Facebook https://www.facebook.com/ahmed.f.gadd Pinterest https://www.pinterest.com/ahmedfgad/

1. Operations in Digital Image
Processing + Convolution by Example
MENOUFIA UNIVERSITY
FACULTY OF COMPUTERS AND INFORMATION
ALL DEPARTMENTS
‫المنوفية‬ ‫جامعة‬
‫والمعلومات‬ ‫الحاسبات‬ ‫كلية‬
‫جميع‬‫األقسام‬
‫المنوفية‬ ‫جامعة‬
Ahmed Fawzy Gad
ahmed.fawzy@ci.menofia.edu.eg

2. Image Processing Operations
Operations
Point Group

3. Point Operations
58 3 213 81 78
185 87 32 27 11
70 66 60 2 19
61 91 129 89 38
14 7 58 14 42
Arithmetic
Operations
+ - * /
Add 2

4. Point Operations
58 3 213 81 78
185 87 32 27 11
70 66 60 2 19
61 91 129 89 38
14 7 58 14 42
Arithmetic
Operations
+ - * /
Add 2

5. Point Operations
60 3 213 81 78
185 87 32 27 11
70 66 60 2 19
61 91 129 89 38
14 7 58 14 42
Arithmetic
Operations
+ - * /
Add 2

6. Point Operations
60 3 213 81 78
185 87 32 27 11
70 66 60 2 19
61 91 129 89 38
14 7 58 14 42
Arithmetic
Operations
+ - * /
Add 2

7. Point Operations
60 5 213 81 78
185 87 32 27 11
70 66 60 2 19
61 91 129 89 38
14 7 58 14 42
Arithmetic
Operations
+ - * /
Add 2

8. Point Operations
60 5 213 81 78
185 87 32 27 11
70 66 60 2 19
61 91 129 89 38
14 7 58 14 42
Arithmetic
Operations
+ - * /
Add 2

9. Point Operations
60 5 215 81 78
185 87 32 27 11
70 66 60 2 19
61 91 129 89 38
14 7 58 14 42
Arithmetic
Operations
+ - * /
Add 2

10. Point Operations
60 5 215 83 80
187 89 34 29 13
72 68 62 4 21
63 93 131 91 40
16 9 60 16 44
Arithmetic
Operations
+ - * /
Add 2

11. Group Operations
58 3 213 81 78
185 87 32 27 11
70 66 60 2 19
61 91 129 89 38
14 7 58 14 42Mode
Median
Mean

12. Group Operations
58 3 213 81 78
185 87 32 27 11
70 66 60 2 19
61 91 129 89 38
14 7 58 14 42Mode
Median
Mean

13. Group Operations
58 3 213 81 78
185 87 32 27 11
70 66 60 2 19
61 91 129 89 38
14 7 58 14 42Mode
Median
Mean
58 + 3 + 213 + 185 + 87 + 32 + 70 + 66 + 60
9
= 𝟖𝟔

14. Group Operations – Template Operations
1 Operation 2 Template
Mode
Median
Mean
7x7
5x5
3x3
ODD
Why odd?

15. Group Operations
58 3 213 81 78
185 87 32 27 11
70 66 60 2 19
61 91 129 89 38
14 7 58 14 42Mode
Median
Mean
58 + 3 + 213 + 185 + 87 + 32 + 70 + 66 + 60
9
= 𝟖𝟔
Put the results in the center.

16. Group Operations
58 3 213 81 78
185 87 32 27 11
70 66 60 2 19
61 91 129 89 38
14 7 58 14 42Mode
Median
Mean
58 + 3 + 213 + 185 + 87 + 32 + 70 + 66 + 60
9
= 𝟖𝟔
Put the results in the center.
𝟖𝟔

17. Group Operations – Even Template Size
58 3 213 81 78
185 87 32 27 11
70 66 60 2 19
61 91 129 89 38
14 7 58 14 42Mode
Median
Mean
58 + 3 + 185 + 87
4
= 𝟖𝟑. 𝟐𝟓 ≅ 𝟖𝟒
Even template sizes has no center.
E.g. 2x3, 2x2, 5x6, …
𝟖𝟒

18. Group Operations – Even Template Size
58 3 213 81 78
185 87 32 27 11
70 66 60 2 19
61 91 129 89 38
14 7 58 14 42Mode
Median
Mean
Even template sizes has no center.
E.g. 2x3, 2x2, 5x6, …
𝟖𝟒
???
58 + 3 + 185 + 87
4
= 𝟖𝟑. 𝟐𝟓 ≅ 𝟖𝟒

19. What is Convolution?
• It is a mathematical way to combine two signals to generate a third
signal. Convolution is not limited on digital image processing and it is
a broad term that works on signals.
Input Signal
Impulse Response
Output Signal
System
Convolution

20. What is Convolution?
• It is a mathematical way to combine two signals to generate a third
signal. Convolution is not limited on digital image processing and it is
a broad term that works on signals.
Input Signal
Impulse Response
Output Signal
System
Convolution
58 3 213 81 78
185 87 32 27 11
70 66 60 2 19
61 91 129 89 38
14 7 58 14 42

21. Convolution for 2D Image Signal
1 3 4 3 10
2 7 4 1 11
6 2 5 2 5
13 6 8 9 1
2 7 12 14 8Template – 3x3
2 1 -4
3 2 5
-1 8 1

22. Convolution for 2D Image Signal
Template – 3x3
2 1 -4
3 2 5
-1 8 1
1 3 4 3 10
2 7 4 1 11
6 2 5 2 5
13 6 8 9 1
2 7 12 14 8

23. Convolution for 2D Image Signal
Template – 3x3
2 1 -4
3 2 5
-1 8 1
1 3 4 3 10
2 7 4 1 11
6 2 5 2 5
13 6 8 9 1
2 7 12 14 8

24. Convolution for 2D Image Signal
1 3 4 3 10
2 44 4 1 11
6 2 5 2 5
13 6 8 9 1
2 7 12 14 8
2 ∗ 1 + 1 ∗ 3 − 4 ∗ 4 + 3 ∗ 2 + 2 ∗ 7 + 5 ∗ 4
− 1 ∗ 6 + 8 ∗ 2 + 1 ∗ 5
= 𝟒𝟒

25. 1 3 4 3 10
2 44 4 1 11
6 2 5 2 5
13 6 8 9 1
2 7 12 14 8
Convolution for 2D Image Signal
2 1 -4
3 2 5
-1 8 1

26. Convolution for 2D Image Signal
2 ∗ 3 + 1 ∗ 4 − 4 ∗ 3 + 3 ∗ 7 + 2 ∗ 4 + 5 ∗ 1
− 1 ∗ 2 + 8 ∗ 5 + 1 ∗ 2
= 𝟕𝟐
1 3 4 3 10
2 44 72 1 11
6 2 5 2 5
13 6 8 9 1
2 7 12 14 8

27. 1 3 4 3 10
2 44 72 1 11
6 2 5 2 5
13 6 8 9 1
2 7 12 14 8
Convolution for 2D Image Signal
2 1 -4
3 2 5
-1 8 1

28. 1 3 4 3 10
2 44 72 2 11
6 2 5 2 5
13 6 8 9 1
2 7 12 14 8
Convolution for 2D Image Signal
2 ∗ 4 + 1 ∗ 3 − 4 ∗ 10 + 3 ∗ 4 + 2 ∗ 1 + 5
∗ 11 − 1 ∗ 5 + 8 ∗ 2 + 1 ∗ 5
= 𝟐

29. 1 3 4 3 10
2 44 72 2 11
6 2 5 2 5
13 6 8 9 1
2 7 12 14 8
Convolution for 2D Image Signal
2 1 -4
3 2 5
-1 8 1

30. 1 3 4 3 10
2 44 72 2 11
6 2 5 2 5
13 6 8 9 1
2 7 12 14 8
Convolution for 2D Image Signal
2 1 -4
3 2 5
-1 8 1

31. 1 3 4 3 10
2 44 72 2 82
6 2 5 2 5
13 6 8 9 1
2 7 12 14 8
Convolution for 2D Image Signal
2 ∗ 3 + 1 ∗ 10 − 4 ∗ 0 + 3 ∗ 2 + 2 ∗ 11 + 5
∗ 0 − 1 ∗ 2 + 8 ∗ 5 + 1 ∗ 0
= 𝟖𝟐

32. 1 3 4 3 10
2 44 72 2 82
6 2 5 2 5
13 6 8 9 1
2 7 12 14 8
Convolution for 2D Image Signal

33. 1 3 4 3 10
2 44 72 2 82
6 2 5 2 5
13 6 8 9 1
2 7 12 14 8
Convolution for 2D Image Signal
2 1 -4
3 2 5
-1 8 1

34. 1 3 4 3 10
2 44 72 2 82
6 2 5 2 5
13 6 8 9 1
2 80 12 14 8
Convolution for 2D Image Signal
2 ∗ 13 + 1 ∗ 6 − 4 ∗ 8 + 3 ∗ 2 + 2 ∗ 7 + 5
∗ 12 − 1 ∗ 0 + 8 ∗ 0 + 1 ∗ 0
= 𝟖𝟎

35. 1 3 4 3 10
2 44 72 2 82
6 2 5 2 5
13 6 8 9 1
2 80 12 14 8
Convolution for 2D Image Signal
2 1 -4
3 2 5
-1 8 1

36. 1 3 4 3 10
2 44 72 2 82
6 2 5 2 5
13 6 8 9 1
2 80 12 14 77
Convolution for 2D Image Signal
2 ∗ 9 + 1 ∗ 1 − 4 ∗ 0 + 3 ∗ 14 + 2 ∗ 8 + 5
∗ 0 − 1 ∗ 0 + 8 ∗ 0 + 1 ∗ 0
= 𝟕𝟕

37. Convolution for 2D Signal
•Continue. 1 3 4 3 10
2 44 72 2 82
6 2 5 2 5
13 6 8 9 1
2 80 12 14 77

38. Convolution for 2D Signal
•Template for Mean.𝟏
𝟗
𝟏
𝟗
𝟏
𝟗
𝟏
𝟗
𝟏
𝟗
𝟏
𝟗
𝟏
𝟗
𝟏
𝟗
𝟏
𝟗
58 3 213 81 78
185 87 32 27 11
70 66 60 2 19
61 91 129 89 38
14 7 58 14 42
𝟏
𝟗
∗ 58 +
𝟏
𝟗
∗ 3 +
𝟏
𝟗
∗ 213 +
𝟏
𝟗
∗ 185 +
𝟏
𝟗
∗ 87 +
𝟏
𝟗
∗ 32
+
𝟏
𝟗
∗ 70 +
𝟏
𝟗
∗ 66 +
𝟏
𝟗
∗ 60
= 86