This document discusses various point operations that can be performed on digital images. Point operations modify pixel values without considering neighboring pixels. The key point operations covered are arithmetic operations like addition/subtraction and multiplication/division, color operations like changing lighting color and swapping/eliminating channels, multiple image operations like combining two images, and histograms which show pixel value distributions. Point operations are useful for image pre-processing tasks like contrast adjustment and color corrections.

1. LECTURE 3
Digital Image Processing

2. POINT OPERATIONS

3. Content
Point Processing
2.1 Introduction …………………………….…………………….
2.2 Arithmetic operations………………………………………
2.3 Color operations………………..…………………………....
2.4 Multiple image operations………………………………..
2.5 Histograms ……………………………….……………………
2.6 Lookup tables………………………………………………...

4. Introduction
Neighborhood processing vs. Point operations

5. Introduction
 Although point operations are the simplest, they
contain some of the most powerful and widely used
of all image processing operations.
 They are especially useful in image pre-processing,
where an image is required to be modified before the
main job is attempted

6. Arithmetic operations
These operations act by applying a simple function
y = f(x)
Types of operations:
1. Addition/Subtraction
2. Multiplications/Division
3. Complementary

7. Addition/Subtraction
To add /subtract a constant from each pixel in the
image.
y = x ± C

8. Addition/Subtraction

9. Multiplications/Division
To multiply /divide each pixel in the image x in/by a
constant c.

10. Multiplications/Division

11. Complementary
The complement of a grey scale image is its
photographic negative.

12. Complementary

13. Image Solarization
Complementing only part of the image.

14. Image Solarization
The image recorded on a negative or on a print is
wholly or partially reversed in tone. Dark areas
appear light or light areas appear dark.

15. Color Images Operations

16. Color Images Operations
Possible channel operations:
 Changing the image lighting color.
 Swapping image channels.
 Eliminating color channels

17. Changing the image lighting color
To change the intensity of one or more
channel by adding or subtracting a constant
R + C => the image will be reddish
 G + C => the image will be greenish
 B + C => the image will be bluish
R,G + C => the image will be yellowish

18. Changing the image lighting color

19. Swapping image channels
To exchange the intensity between the image
channels.
 R , G => the image will be GRB
 G , B => the image will be RBG
 B , R => the image will be BGR
Other spaces could be obtained by swapping
2 channels at once like; GBR and BRG.

20. Swapping image channels

21. Eliminating color channels
To set one or more color channels by zero
values.
 Eliminating R => image will be in cyan
 Eliminating G => image will be in magenta
 Eliminating B => image will be in yellow
 Eliminating R,G => image will be in blue
 Eliminating G,B => image will be in red
 Eliminating B,R => image will be in green

22. Eliminating color channels

23. Multiple Image Operations
Perform operations between two images or
more for:
1. Enhance the image visual appeal.
2. Getting specific part of image between similar
images.(eg. motion tracking)
3. For some preprocessing purposes.

24. Multiple Image Operations
Assume two images x1 and x2: the possible
operations between x1 and x2:

25. Example

26. Operation Results

27. Image Histogram
It is a graph indicating the number of times
each grey level occurs in the image.

28. Color Image Histogram

29. Color Image Histogram

30. Why Histogram?
To know image features:
 Most color(intensity) in the image
 Image Contrast
 Image Brightness
For segmentation purpose
 A threshold can be used to segment the image into
parts.

31. Histogram Image features
In a dark image, the grey levels would be
clustered at the lower end.
In a uniformly bright image, the grey levels
would be clustered at the upper end.
In a well contrasted image, the grey levels
would be well spread out over much of the
range.