DIGITAL IMAGE PROCESSING
Course Code : 18EC733
CIE Marks :40
Lecture Hours/Week : 3
SEE Marks :60
Total Number of Lecture Hours : 40 (08 Hrs / Module)
Exam Hours :03
CREDITS — 03
Course Learning Objectives: This course will enable students to
- Understand the fiindamentals of digital image processing.
- Understand the image transforms used in digital image processing.
- Understand the image enhancement techniques used in digital image processing.
- Understand the image restoration techniques and methods used in digital image processing.
- Understand the Morphological Operations used in digital image processing.
Module1
Digital Image Fundamentals: Whatis 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. (Text: Chapter 1 and Chapter 2: Sections 2.1 to 2.2, 2.6.2) L1,L2Notes link given below
Module-2
Image Enhancement in the Spatial Domain: Image Sampling and Quantization, Some Basic Relationships Between Pixels, Linear and Nonlinear Operations. Some Basic Intensity Transformation Functions, Histogram Processing, Fundamentals of Spatial Filtering, Smoothing Spatial Filters, Sharpening Spatial Filters (TextzChapterZ: Sections 2.3 to 2.62, Chapter3: Sections3.2 to 3.6), L1,L2Notes link given below
Module-3
Frequency Domain: Preliminary Concepts, The Discrete Fourier Transform (DFT) of Two Variables, Properties of the 2-DDFT, Filtering in the Frequency Domain, Image Smoothing and Image Sharpening Using Frequency Domain Filters, Selective Filtering. (Text: Chapter4: Sections 4.2, 4.5 to 4.10), L1,L2Notes link given below
Module-4
Restoration: Noise models, Restorationin the Presence of Noise Only using Spatial Filtering and Frequency Domain Filtering, Linear, Position-Invariant degradations Estimating the Degradation Function, Inverse Filtering, Minimum Mean Square Error(Wiener) Filtering, Constrained Least Squares Filtering. (Text: Chapter 5: Sections 5.2, to 5.9) L1,L2Notes link given below
Module-5
Morphological Image Processing: Preliminaries, Erosion and Dilation, Opening and Closing. Image Processing: Color Fundamentals, Color Models, Pseudo color Image Processing. (Text: Chapter 6: Sections 6.1 to 6.3 Chapter 9: Sections9.1to9.3) L1,L2Click Here to Download Full Notes
Course Outcomes: At the end of the course, students should be able to:
1. Describe the fundamentals of digital image processing.2. Understand image formation and the role human Visual system plays in perception of gray and color image data.
3. Apply image processing techniques in both the spatial and frequency (Fourier) domains.
4. Design and evaluate image analysis techniques
5. Conduct independent study and analysis of Image Enhancement and restoration techniques.
Question paper pattern:
- The examination will be conducted for 100 marks with question paper containing 10 full questions, each of 20 marks.
- Each fiill question can have a maximum of 4 sub questions.
- There will be 2 filll questions from each module covering all the topics of the module.
- Students will have to answer 5 filll questions, selecting one full questionfiom each module.
- The total marks will be proportionally reduced to 60 marks as SEE marks is 60.
Text Book:
Digital Image Processing- Rafel C Gonzalez and Richard E. Woods, PHI3'“ Edition 2010.Reference Books:
1. Digital Image Processing- S. J ayaraman, S. Esakkiraj an,T. Veerakumar, Tata Mc Graw Hill 2014.2. Fundamentals of Digital Image Processing- A. K. Jain, Pearson 2004.
3 Image Processing analysis and Machine Vision with Mind Tap by Milan Sonka and Roger Boile, Cengage Publications, 2018.
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