8 CS 4.2-IMAGE PROCESSING |
Units: I |
Introduction and Fundamentals: Motivation and Perspective, Applications, Components of Image Processing System,
Element of Visual Perception, A Simple Image Model, Sampling and Quantization. Image Enhancement in Spatial Domain:
Introduction; Basic Gray Level Functions – Piecewise-Linear Transformation Functions: Contrast Stretching; Histogram
Specification; Histogram Equalization; Local Enhancement; Enhancement using Arithmetic/Logic Operations –
Image Subtraction, Image Averaging; Basics of Spatial Filtering; Smoothing - Mean filter, Ordered Statistic Filter;
Sharpening – The Laplacian.
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Units: II |
Image Enhancement in Frequency Domain: Fourier Transform and the Frequency Domain, Basis of Filtering in
Frequency Domain, Filters – Low-pass, High-pass; Correspondence Between Filtering in Spatial and Frequency
Domain; Smoothing Frequency Domain Filters – Gaussian Low pass Filters; Sharpening Frequency Domain Filters – Gaussian High pass Filters; Homomorphic Filtering. Image Restoration: A Model of Restoration Process, Noise Models,
Restoration in the presence of Noise only Spatial Filtering – Mean Filters: Arithmetic Mean filter, Geometric Mean Filter,
Order Statistic Filters – Median Filter, Max and Min filters; Periodic Noise Reduction by Frequency Domain Filtering – Band
pass Filters; Minimum Mean- square Error Restoration. |
Units: III |
Color Image Processing: Color Fundamentals, Color Models, Converting Colors to different models, Color
Transformation, Smoothing and Sharpening, Color Segmentation. Morphological Image Processing: Introduction, Logic
Operations involving Binary Images, Dilation and Erosion, Opening and Closing, Morphological Algorithms – Boundary
Extraction, Region Filling, Extraction of Connected Components, Convex Hull, Thinning, Thickening.
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Units: IV |
Registration: Introduction, Geometric Transformation – Plane to Plane transformation, Mapping, Stereo Imaging –
Algorithms to Establish Correspondence, Algorithms to Recover Depth. Segmentation: Introduction, Region Extraction,
Pixel-Based Approach, Multi-level Thresholding, Local Thresholding, Region-based Approach, Edge and Line Detection:
Edge Detection, Edge Operators, Pattern Fitting Approach, Edge Linking and Edge Following, Edge Elements Extraction by
Thresholding, Edge Detector Performance, Line Detection, Corner Detection.
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Units: V |
Feature Extraction: Representation, Topological Attributes, Geometric Attributes. Description: Boundary-based Description,
Region-based Description, Relationship. Object Recognition: Deterministic Methods, Clustering, Statistical Classification,
Syntactic Recognition, Tree Search, Graph Matching.
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