This document discusses various digital image processing techniques. It covers connected component labeling, intensity transformations including linear, logarithmic and power law functions. It also describes spatial domain vs transform domain processing and examples of enhancement techniques like contrast stretching and intensity-level slicing. Finally, it discusses geometric transformations and image registration to align images.

1. Digital Image
Processing

2. Connected component

3. Connected component labeling
the process of identifying the connected
components in an image and assigning each
one a unique label, like this:

8. Intensity Transformation

9. Contents
Spatial domain vs. Transform domain
Enhancement
Intensity transformation functions
Linear
Logarithmic
Power law
Piecewise-Linear Transformation function
Contrast stretching
Intensity-level slicing
Bit-plane slicing

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Spatial Domain vs. Transform Domain
Spatial domain
image plane itself, directly process the intensity values of the
image plane
Transform domain
process the transform coefficients, not directly process the
intensity values of the image plane

11. Enhancement
To manipulate an image so that the result is
more suitable than the original for a specific
application
Problem oriented

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Spatial Domain Process
( , ) [ ( , )])
( , ):input image
( , ):output image
:an operator on defined over
a neighborhood of point ( , )
g x y T f x y
f x y
g x y
T f
x y


13. Spatial Operations
Point/Pixel operations
Output value at specific coordinates (x,y)
is dependent only on the input value at
(x,y)
Local/neighborhood operations
The output value at (x,y) is dependent on
the input values in the neighborhood of
(x,y)
Geometric spatial transformations
Affine transformation
Image Registration

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Point/Pixel operations
Intensity transformation function
( )s T r

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Local/neighborhood operation

16. Local/neighborhood operation

17. Geometric/Spatial transformation
.

19. Image Registration
One of the most important applications of geometric
transformations is image registration
Goal: Image registration seeks to align images taken in
different times, or taken from different
How: estimate a transformation that aligns the two or
more images.
Image registration has applications especially in
• Medicine
• Remote sensing
• Entertainment

20. Image Registration
Background—Example, Panorama Stitching

21. Image Registration

22. Image Registration

23. Intensity transformation functions
Linear
Negative
Identity
Logarithmic
Log transform
Inverse Log transform
Power law
nth power
nth root

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Some Basic Intensity Transformation Functions

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Image Negatives
Image negatives
1s L r  

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Example: Image Negatives

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Log Transformations
Log Transformations
log(1 )s c r 

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Example: Log Transformations

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Power-Law (Gamma) Transformations
s cr


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Example: Gamma Transformations

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Example: Gamma Transformations
1/2.5
s r

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Example: Gamma Transformations

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Example: Gamma Transformations

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Piecewise-Linear Transformations
Contrast Stretching
Expands the range of intensity levels in an image
so that it spans the full intensity range of the
recording medium or display device.
Intensity-level Slicing
Highlighting a specific range of intensities in an image
often is of interest.

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Highlight the major blood
vessels and study the
shape of the flow of the
contrast medium (to detect
blockages, etc.)
Measuring the actual flow
of the contrast medium as
a function of time in a
series of images

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Bit-plane Slicing

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Bit-plane Slicing

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Bit-plane Slicing