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Image Processing (CA-507)
Unit 1. Introduction
Session 1 : Definition of Digital Image Processing
Session 2 : Origins of Digital Image Processing
Session 3 : Examples of fields that use Digital Image Processing - X-ray Imaging
Session 4 : Ultraviolet Band
Session 5 : Visible and Infrared Bands
Session 6 : Microwave Band
Session 7 : Radio Band Imaging
Session 8 : Fundamental Steps in Digital Image Processing
Session 9 : Components of an Image Processing System
Unit 2. Digital Image Fundamentals
Session 10 : Elements of Visual Perception
Session 11 : Light and the Electromagnetic Spectrum
Session 12 : Image Sensing and Acquisition - Single Sensor
Session 13 : Sensor Strips
Session 14 : Sensor Arrays
Session 15 : A Simple Image Formation Model
Session 16 : Image Sampling and Quantization - Spatial and Gray-Level Resolution
Session 17 : Aliasing
Session 18 : Some Basic Relationships between Pixels - Neighbors
Session 19 : Adjacency
Session 20 : Connectivity
Session 21 : Regions
Session 22 : Boundaries
Session 23 : Distance Measures
Session 24 : Image Operations on a Pixel Basis
Session 25 : Linear and Nonlinear Operations
Unit 3. Image Enhancement in the Spatial Domain
Session 26 : Some Basic Gray Level Transformations - Negatives
Session 27 : Log
Session 28 : Power-Law
Session 29 : Piecewise- Linear Transformations
Session 30 : Histogram Processing - Histogram Equalization
Session 31 : Enhancement Using Arithmetic/Logic Operations – Image Subtraction
Session 32 : Image Averaging
Session 33 : Basics of Spatial Filtering
Session 34 : Smoothing Spatial Filters – Smoothing Linear and Order-Statistics Filters
Session 35 : Sharpening Spatial Filters - Use of First Derivatives for Enhancement
Session 36 : Use of Second Derivatives for Enhancement : The Laplacian
Session 37 : High Boost Filtering
Session 38 : High Frequency Emphasis Filtering
Session 39 : Introduction to the Fourier Transform and the Frequency Domain
Unit 4. Image Enhancement in the Frequency Domain
Session 40 : Two-Dimensional DFT and its Inverse
Session 41 : Some Properties of the 2-D Fourier Transform
Session 42 : Filtering in the Frequency Domain
Session 43 : Correspondence between Filtering in the Spatial and Frequency Domains
Session 44 : The Convolution Theorem(Only 2D)
Session 45 : Frequency-Domain Lowpass Filters - Ideal
Session 46 : Butterworth and Gaussian Frequency Domain Highpass Filters - Ideal
Session 47 : Butterworth, and Gaussian Unsharp Masking
Session 48 : High-Boost Filtering
Session 49 : High-Frequency Emphasis Filtering
Unit 5. Image Restoration
Session 50 : A Model of the Image Degradation/Restoration Process
Session 51 : Noise Models
Session 52 : Restoration in the Presence of Noise Only – Spatial Filtering - Mean
Session 53 : Order-Statistics
Session 54 : Adaptive Filters
Session 55 : Periodic Noise Reduction by Frequency Domain Filtering – Band reject
Session 56 : Band pass
Session 57 : Notch Filters
Session 58 : Estimating the Degradation Function - Estimation by Image Observation
Session 59 : Experimentation and Modeling
Session 60 : Inverse Filtering
Session 61 : Geometric Mean Filter - Geometric Transformations
Session 62 : Spatial Transformations
Unit 6. Morphological Image Processing
Session 63 : Some Basic Concepts from Set Theory
Session 64 : Logic Operations Involving Binary Images
Session 65 : Dilation and Erosion
Session 66 : Opening and Closing
Session 67 : The Hit-or-Miss Transformation
Session 68 : Some Basic Morphological Algorithms - Boundary Extraction
Session 69 : Region Filling
Session 70 : Extraction of Connected Components
Session 71 : Thinning
Session 72 : Thickening
Unit 7. Image Segmentation
Session 73 : Detection of Discontinuities - Point Detection
Session 74 : Line Detection
Session 75 : Edge Detection
Session 76 : Edge Linking and Boundary Detection
Session 77 : Thresholding- The Role of Illumination
Session 78 : Basic Global Thresholding
Session 79 : Basic Adaptive Thresholding
Session 80 : Region-Based Segmentation -Region Growing
Session 81 : Region Splitting and Merging
Unit 8 : Representation and Description
Session 82 : Chain Codes
Session 83 : Polygonal Approximations
Session 84 : Signatures
Session 85 : Shape Methods (Mathematical Problems)
Session 58 : Estimating the Degradation Function - Estimation by Image Observation
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