UG CONSULTANTS

Digital Image Processing

Course Contents

UNIT 1

Digital Image Representation

  • Coordinate Conventions
  • Images as Matrices
  • Reading Images
  • Displaying Images
  • Writing Images
  • Classes
  • Image Types
  • Gray-scale Images
  • Binary Images
  • A Note on Terminology
  • Converting between Classes
  • Array Indexing
  • Indexing Vectors
  • Indexing Matrices
  • Indexing with a Single Colon
  • Logical Indexing
  • Linear Indexing
  • Selecting Array Dimensions
  • Sparse Matrices
  • Some Important Standard Arrays
  • Introduction to M-Function Programming
  • M-Files
  • Operators
  • Flow Control
  • Function Handles
  • Code Optimization
  • Interactive I/O
  • An Introduction to Cell Arrays and Structures

UNIT 2

Intensity Transformations and Spatial Filtering

  • Intensity Transformation Functions
  • Functions imadjustand stretchlim
  • Logarithmic and Contrast-Stretching Transformations
  • Specifying Arbitrary Intensity Transformations
  • Some Utility M-functions for Intensity Transformations
  • Histogram Processing and Function Plotting
  • Generating and Plotting Image Histograms
  • Histogram Equalization
  • Histogram Matching (Specification)
  • Function adapthisteq
  • Spatial Filtering
  • Linear Spatial Filtering
  • Nonlinear Spatial Filtering
  • Image Processing Toolbox Standard Spatial Filters
  • Linear Spatial Filters
  • Nonlinear Spatial Filters
  • Using Fuzzy Techniques for Intensity Transformations and Spatial Filtering
  • Background
  • Introduction to Fuzzy Sets
  • Using Fuzzy Sets
  • A Set of Custom Fuzzy M-functions
  • Using Fuzzy Sets for Intensity Transformations
  • Using Fuzzy Sets for Spatial Filtering

UNIT 3

Filtering in the Frequency Domain

  • The 2-D Discrete Fourier Transform
  • Computing and Visualizing the 2-D DFT in MATLAB
  • Filtering in the Frequency Domain
  • Fundamentals 173
  • Basic Steps in DFT Filtering
  • An M-function for Filtering in the Frequency Domain
  • Obtaining Frequency Domain Filters from Spatial Filters
  • Generating Filters Directly in the Frequency Domain
  • Creating Meshgrid Arrays for Use in Implementing Filters in the Frequency Domain
  • Lowpass (Smoothing) Frequency Domain Filters
  • Wireframe and Surface Plotting
  • Highpass (Sharpening) Frequency Domain Filters
  • A Function for Highpass Filtering
  • High-Frequency Emphasis Filtering
  • Selective Filtering
  • Bandreject and Bandpass Filters
  • Notchreject and Notchpass Filters

UNIT 4

Image Restoration and Reconstruction

  • A Model of the Image Degradation/Restoration Process
  • Noise Models
  • Adding Noise to Images with Function imnoise()
  • Generating Spatial Random Noise with a Specified Distribution
  • Periodic Noise
  • Estimating Noise Parameters
  • Restoration in the Presence of Noise Only—Spatial Filtering
  • Spatial Noise Filters
  • Adaptive Spatial Filters
  • Periodic Noise Reduction Using Frequency Domain Filtering
  • Modeling the Degradation Function
  • Direct Inverse Filtering
  • Wiener Filtering
  • Constrained Least Squares (Regularized) Filtering
  • Iterative Nonlinear Restoration Using the Lucy-Richardson Algorithm
  • Blind Deconvolution
  • Image Reconstruction from Projections
  • Background
  • Parallel-Beam Projections and the Radon Transform
  • The Fourier Slice Theorem and Filtered Backprojections
  • Filter Implementation
  • Reconstruction Using Fan-Beam Filtered Backprojections
  • Function radon()
  • Function iradon()
  • Working with Fan-Beam Data

UNIT 5

Geometric Transformations and Image Registration

  • Transforming Points
  • Affine Transformations
  • Projective Transformations
  • Applying Geometric Transformations to Images
  • Image Coordinate Systems in MATLAB
  • Output Image Location
  • Controlling the Output Grid
  • Image Interpolation
  • Interpolation in Two Dimensions
  • Comparing Interpolation Methods
  • Image Registration
  • Registration Process
  • Manual Feature Selection and Matching Using cpselect
  • Inferring Transformation Parameters Using cp2tform
  • Visualizing Aligned Images
  • Area-Based Registration
  • Automatic Feature-Based Registration

UNIT 6

Color Image Processing

  • Color Image Representation in MATLAB
  • RGB Images
  • Indexed Images
  • Functions for Manipulating RGB and Indexed Images
  • Converting Between Color Spaces
  • NTSC Color Space
  • The YCbCr Color Space
  • The HSV Color Space
  • The CMY and CMYK Color Spaces
  • The HSI Color Space
  • Device-Independent Color Spaces
  • The Basics of Color Image Processing
  • Color Transformations
  • Spatial Filtering of Color Images
  • Color Image Smoothing
  • Color Image Sharpening
  • Working Directly in RGB Vector Space
  • Color Edge Detection Using the Gradient
  • Image Segmentation in RGB Vector Space

UNIT 7

Wavelets

  • The Fast Wavelet Transform
  • FWTs Using the Wavelet Toolbox
  • FWTs without the Wavelet Toolbox
  • Working with Wavelet Decomposition Structures
  • Editing Wavelet Decomposition Coefficients without the Wavelet Toolbox
  • Displaying Wavelet Decomposition Coefficients
  • The Inverse Fast Wavelet Transform
  • Wavelets in Image Processing

UNIT 8

Image Compression

  • Coding Redundancy
  • Huffman Codes
  • Huffman Encoding
  • Huffman Decoding
  • Spatial Redundancy
  • Irrelevant Information
  • JPEG Compression
  • JPEG
  • JPEG 2000
  • Video Compression
  • MATLAB Image Sequences and Movies
  • Temporal Redundancy and Motion Compensation

UNIT 9

Morphological Image Processing

  • Some Basic Concepts from Set Theory
  • Binary Images, Sets, and Logical Operators
  • Dilation and Erosion
  • Dilation
  • Structuring Element Decomposition
  • The strel Function
  • Erosion
  • Combining Dilation and Erosion
  • Opening and Closing
  • The Hit-or-Miss Transformation
  • Using Lookup Tables
  • Function bwmorph
  • Labeling Connected Components
  • Morphological Reconstruction
  • Opening by Reconstruction
  • Filling Holes
  • Clearing Border Objects
  • Gray-Scale Morphology
  • Dilation and Erosion
  • Opening and Closing
  • Reconstruction

UNIT 10

Image Segmentation

  • Point, Line, and Edge Detection
  • Point Detection
  • Line Detection
  • Edge Detection Using Function edge
  • Line Detection Using the Hough Transform
  • Background
  • Toolbox Hough Functions
  • Thresholding
  • Foundation
  • Basic Global Thresholding
  • Optimum Global Thresholding Using Otsu's Method
  • Using Image Smoothing to Improve Global Thresholding
  • Using Edges to Improve Global Thresholding
  • Variable Thresholding Based on Local Statistics
  • Image Thresholding Using Moving Averages
  • Region-Based Segmentation
  • Basic Formulation
  • Region Growing
  • Region Splitting and Merging
  • Segmentation Using the Watershed Transform
  • Watershed Segmentation Using the Distance Transform
  • Watershed Segmentation Using Gradients
  • Marker-Controlled Watershed Segmentation

UNIT 11

Representation and Description

  • Functions for Extracting Regions and Their Boundaries
  • Some Additional MATLAB and Toolbox Functions
  • Some Basic Utility M-Functions
  • Representation
  • Chain Codes
  • Polygonal Approximations Using Minimum-Perimeter Polygons
  • Signatures
  • Boundary Segments
  • Skeletons
  • Boundary Descriptors
  • Some Simple Descriptors
  • Shape Numbers
  • Fourier Descriptors
  • Statistical Moments
  • Corners
  • Regional Descriptors
  • Function regionprops()
  • Texture
  • Moment Invariants
  • Using Principal Components for Description

UNIT 12

Object Recognition

  • Computing Distance Measures in MATLAB
  • Recognition Based on Decision-Theoretic Methods
  • Forming Pattern Vectors
  • Pattern Matching Using Minimum-Distance Classifiers
  • Matching by Correlation
  • Optimum Statistical Classifiers
  • Adaptive Learning Systems
  • Structural Recognition
  • Working with Strings in MATLAB
  • String Matching