Digital image processing involves processing digital images through computer software and hardware. It has several key stages including image acquisition, restoration, enhancement, segmentation, representation and description, object recognition, and compression. It is used for a variety of applications like improving images for human perception, enabling machine vision in industries, and efficient storage and transmission of images. Some common techniques include noise filtering, contrast enhancement, blurring removal, and edge detection which are used in applications such as medical imaging, industrial inspection, and human-computer interaction.

1. Digital image
processing
RAVI JINDAL
Joint Masters, SEGE (M1) Second semester
B.K. Birla institute of Engineering &
Technology, Pilani
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2. What is a digital image?
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3.  Processing of images which are Digital in nature by a
Digital computer
 Common image formats include:
– 1 sample per point (B&W or Gray scale)
– 3 samples per point (Red, Green, and Blue)
– 4 samples per point (Red, Green, Blue, and “Alpha”,
Opacity)
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4. Why we need image processing?
It is motivated by three major application
Improvement of pictorial information for human
perception
Image processing for autonomous machine application
Efficient storage and transmission
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5. Key Stages in Digital Image Processing
Image
Acquisition
Image
Restoration
Segmentation
Representation
& Description
Image
Enhancement
Object
Recognition
Problem Domain
Colour Image
Processing
Image
Compression
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6. Key Stages in Digital Image Processing:
Image Acquisition
Image
Acquisition
Image
Restoration
Morphological
Processing
Segmentation
Representation
& Description
Image
Enhancement
Object
Recognition
Problem Domain
Colour Image
Processing
Image
Compression
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7. Key Stages in Digital Image Processing:
Image Enhancement
Image
Acquisition
Image
Restoration
Morphological
Processing
Segmentation
Representation
& Description
Image
Enhancement
Object
Recognition
Problem Domain
Colour Image
Processing
Image
Compression
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8. Image
Acquisition
Image
Restoration
Segmentation
Representation
& Description
Image
Enhancement
Object
Recognition
Problem Domain
Colour Image
Processing
Image
Compression
Key Stages in Digital Image Processing:
Image Restoration
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9. Image
Acquisition
Image
Restoration
Segmentation
Representation
& Description
Image
Enhancement
Object
Recognition
Problem Domain
Colour Image
Processing
Image
Compression
Key Stages in Digital Image Processing:
Segmentation
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10. Key Stages in Digital Image Processing:
Object Recognition
Image
Acquisition
Image
Restoration
Segmentation
Representation
& Description
Image
Enhancement
Object
Recognition
Problem Domain
Colour Image
Processing
Image
Compression
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11. Key Stages in Digital Image Processing:
Representation & Description
Image
Acquisition
Image
Restoration
Segmentation
Representation
& Description
Image
Enhancement
Object
Recognition
Problem Domain
Colour Image
Processing
Image
Compression
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12. Key Stages in Digital Image Processing:
Image Compression
Image
Acquisition
Image
Restoration
Segmentation
Representation
& Description
Image
Enhancement
Object
Recognition
Problem Domain
Colour Image
Processing
Image
Compression
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13. Key Stages in Digital Image Processing:
Colour Image Processing
Image
Acquisition
Image
Restoration
Segmentation
Representation
& Description
Image
Enhancement
Object
Recognition
Problem Domain
Colour Image
Processing
Image
Compression
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14. Human perception
 Employ method is capable of enhancing pictorial
information for human interpretation and analysis
 Typical application :-
 Noise filter
 content enhancement
 contrast enhancement
 DE blurring
 remote sensing
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15. Filtering
Filtered Image
Noisy Image
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16. Image Enhancement
Enhanced Image
Low Contrast Image
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17. Image Enhancement
Enhanced Image
Low Contrast Image
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18. Image DE blurring
Defocused Motion Blurred
DE blurred 18

19. 
Human operators are
expensive, slow and
unreliable
Make machines do the
job instead Industrial
vision systems are used
in all kinds of industries
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Industrial Inspection

20. Medicine
• Take slice from MRI scan of canine heart, and find
boundaries between types of tissue
• Image with grey levels representing tissue density
• Use a suitable filter to highlight edges
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Original MRI Image of a Dog Heart Edge Detection Image

21.  Try to make human computer interfaces
more natural
Face recognition
Gesture recognition Does anyone remember
the user interface from “Minority Report”?
These tasks can be extremely difficult
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Examples: HCI

22. References
• http://www.owlnet.rice.edu/~elec539/Projects99/BACH/p
roj2/intro.html
• https://www.cs.auckland.ac.nz/courses/compsci773s1c/le
ctures/ImageProcessing-html/topic3.htm
• http://freevideolectures.com/Course/2316/Digital-Image-
Processing-IIT-Kharagpur#
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23. Thank You 
• rjindal21@gmail.com
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