Digital Image Processing
What is digital image Processing
• Digital Image Processing means processing
digital image by means of a digital computer.
Why do we need image processing
• Improvement of pictorial information for
human perception.
• Image processing for autonomous machine
application
• Efficient storage and transmission
Fundamentals steps in image processing
Applications
Fingerprint Verification /
Identification
Object Recognition Research
reference view 1 reference view 2
novel view recognized
Indexing into Databases (cont’d)
Target Recognition
Department of Defense (Army, Airforce, Navy)
Autonomous Vehicles
Traffic Monitoring
Face Detection
Facial Expression Recognition
Human Activity Recognition
•
Inserting Artificial Objects into a Scene- Augmented
reality
•
Image Processing Companies
• Scandit.
• SenseTime.
• Descartes Labs.
• NVIDIA Corporation.
• AYLIEN.
• Reality AI.
• CNRS, The French National Center for
Scientific Research.
Image Processing Companies
•Zebra Technologies TCS
•Huawei NVIDIA
•Canon Google
•Bosch Amazon
•Siemens Apple
•Infosys Scandit
•Wipro Sensetime
•Medtronic
•Xilinx
•Samsung
•Adobe
•Sony
Module 1
• Digital Image Fundamentals: What is Digital
Image Processing?, Origins of Digital Image
Processing, Examples of fields that use DIP,
Fundamental Steps in Digital Image Processing,
Components of an Image Processing System,
Elements of Visual Perception, Image Sensing and
Acquisition, Image Sampling and Quantization,
Some Basic Relationships Between Pixels.
• [Text 1: Chapter 1, Chapter 2: Sections 2.1 to 2.5]
Module 2
• Image Transforms: Introduction, Two-
Dimensional Orthogonal and Unitary Transforms,
Properties of Unitary Transforms, Two-
Dimensional DFT, cosine Transform, Haar
Transform.
• Text 2: Chapter 5: Sections 5.1 to 5.3, 5.5, 5.6,
5.9]
Module 3
• Spatial Domain: Some Basic Intensity
Transformation Functions, Histogram
Processing,
• Fundamentals of Spatial Filtering, Smoothing
Spatial Filters, Sharpening Spatial Filters [Text:
Chapter 3: Sections 3.2 to 3.6]
Module 4
• Frequency Domain: Basics of Filtering in the
Frequency Domain, Image Smoothing and
Image Sharpening Using Frequency Domain
Filters.
• Color Image Processing: Color Fundamentals,
Color Models, Pseudo-color Image Processing.
• [Text 1: Chapter 4: Sections 4.7 to 4.9 and
Chapter 6: Sections 6.1 to 6.3]
Module 5
• Restoration: A model of the Image
Degradation/Restoration Process, Noise models,
Restoration in the Presence of Noise Only using
Spatial Filtering and Frequency Domain Filtering,
Inverse Filtering, Minimum Mean Square Error
(Wiener) Filtering.
• [Text 1: Chapter 5: Sections 5.1, to 5.4.3, 5.7,
5.8]
Course Outcomes
• Understand image formation and the role of human
visual system plays in perception of gray and color
image data.
• Compute various transforms on digital images.
• Conduct independent study and analysis of Image
Enhancement techniques.
• Apply image processing techniques in frequency
(Fourier) domain.
• Design image restoration techniques.
Text Books:
1. Digital Image Processing- Rafael C Gonzalez and
Richard E Woods, PHI, 3rd Edition 2010.
2. Fundamentals of Digital Image Processing- A K
Jain, PHI Learning Private Limited 2014.
Reference Book:
3. Digital Image Processing- S Jayaraman, S
Esakkirajan, T Veerakumar, Tata McGraw Hill,
2014.
Thank you
