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.
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
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.
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
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.
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
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.
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.