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Kalamassery, Kochi, Ernakulam
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Electronics & Communication Engineering
Digital Image Processing
Digital Image Processing
Curriculum
6 Sections
22 Lessons
4 Weeks
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Module 1
Fundamentals of image processing
6
1.1
Fundamentals of Image Processing
1.2
Quiz on fundamentals
5 Minutes
3 Questions
1.3
Basic Relationship between pixels
1.4
Elements of Digital Image Processing
1.5
Color Image Fundamentals
1.6
Image Sampling and Quantization
Module 2
Review of matrix theory-2D Image transforms-Image Compression
5
2.1
Matrix Theory
2.2
Need for compression- Redundancy- Classification
2.3
Some coding techniques- DFT and its properties
2.4
Few Transforms
2.5
Few Problems and Transform Based coding
Module 3
Image Enhancement
5
3.1
Image Enhancement- Introduction, Some Basic Intensity transformation
3.2
Spatial Filters
3.3
Frequency Domain Filtering
3.4
Homomorphic filtering- Image Subtraction- Image Averaging
3.5
Histogram Processing- Various Problems
Module 4
Image restoration
3
4.1
Image Restoration- Constrained and Unconstrained- Inverse filtering- Removal of Blur by Uniform Linear Motion
4.2
Geometric Transformation- Model- Weiner Filter
4.3
Causes of Blur- Types of Blur- Classification of Restoration
Module 5
Image Segmentation
4
5.1
Types of Image segmentation- Region Based segmentation
5.2
Region Splitting and Merging
5.3
Edge based segmentation
5.4
Clustering
0
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