Mathematical Background for Image Processing: Review of Vectors and Matrices
- Review of Probability and statistics. Digital Image Fundamentals: Elements of Visual Perception - Image Sensing and Acquisition – Image Sampling and Quantization
– Basic Relationships between Pixels - Image interpolation. Intensity Transformations
and Spatial Filtering: Basic Intensity transformation Functions – Histogram Processing
– Fundamentals of Spatial Filtering – Smoothing and Sharpening Spatial Filters.
Filtering in Frequency Domain: 2D Discrete Fourier Transforms - Basics of filtering
- Image Smoothing and Image Sharpening Using Frequency Domain Filters - Selective
Filtering, Image Restoration: Noise Models – Restoration using Spatial Filters –
Periodic Noise Reduction by Frequency Domain Filters.
Morphological Image Processing: Erosion – Dilation – Opening – Closing – Hit-orMiss Transform - Extraction of Connected Components. Image Segmentation:
Fundamentals – Point, Line and Edge Detection – Thresholding - Region Based
Segmentation – Region Growing – Region Splitting and Merging. Color image processing.