Book description
Uptodate, technically accurate coverage of essential topics in image and video processing
This is the first book to combine image and video processing with a practical MATLAB®oriented approach in order to demonstrate the most important image and video techniques and algorithms. Utilizing minimal math, the contents are presented in a clear, objective manner, emphasizing and encouraging experimentation.
The book has been organized into two parts. Part I: Image Processing begins with an overview of the field, then introduces the fundamental concepts, notation, and terminology associated with image representation and basic image processing operations. Next, it discusses MATLAB® and its Image Processing Toolbox with the start of a series of chapters with handson activities and stepbystep tutorials. These chapters cover image acquisition and digitization; arithmetic, logic, and geometric operations; pointbased, histogrambased, and neighborhoodbased image enhancement techniques; the Fourier Transform and relevant frequencydomain image filtering techniques; image restoration; mathematical morphology; edge detection techniques; image segmentation; image compression and coding; and feature extraction and representation.
Part II: Video Processing presents the main concepts and terminology associated with analog video signals and systems, as well as digital video formats and standards. It then describes the technically involved problem of standards conversion, discusses motion estimation and compensation techniques, shows how video sequences can be filtered, and concludes with an example of a solution to object detection and tracking in video sequences using MATLAB®.
Extra features of this book include:
More than 30 MATLAB® tutorials, which consist of stepbystep guides to exploring image and video processing techniques using MATLAB®
Chapters supported by figures, examples, illustrative problems, and exercises
Useful websites and an extensive list of bibliographical references
This accessible text is ideal for upperlevel undergraduate and graduate students in digital image and video processing courses, as well as for engineers, researchers, software developers, practitioners, and anyone who wishes to learn about these increasingly popular topics on their own.
Table of contents
 Cover
 Title Page
 Copyright
 Dedication
 List of Figures
 List of Tables
 Foreword
 Preface
 Acknowledgments

Part I: Image Processing
 Chapter 1: Introduction and Overview
 Chapter 2: Image Processing Basics

Chapter 3: Matlab Basics
 What will we Learn?
 3.1 Introduction to MATLAB
 3.2 Basic Elements of MATLAB
 3.3 Programming Tools: Scripts and Functions
 3.4 Graphics and Visualization
 3.5 Tutorial 3.1: MATLAB—a Guided Tour
 3.6 Tutorial 3.2: MATLAB data Structures
 3.7 Tutorial 3.3: Programming in MATLAB
 What have we Learned?
 Learn More About It
 On the Web
 3.8 Problems
 Chapter 4: The Image Processing Toolbox at a Glance
 Chapter 5: Image Sensing and Acquisition
 Chapter 6: Arithmetic and Logic Operations

Chapter 7: Geometric Operations
 What Will we Learn?
 7.1 Introduction
 7.2 Mapping and Affine Transformations
 7.3 Interpolation Methods
 7.4 Geometric Operations Using MATLAB
 7.5 Other Geometric Operations and Applications
 7.6 Tutorial 7.1: Image Cropping, Resizing, Flipping, and Rotation
 7.7 Tutorial 7.2: Spatial Transformations and Image Registration
 What have we Learned?
 Learn More About it
 On the Web
 7.8 Problems
 Chapter 8: GrayLevel Transformations

Chapter 9: Histogram Processing
 What will we learn?
 9.1 Image histogram: definition and example
 9.2 Computing image histograms
 9.3 Interpreting image histograms
 9.4 Histogram equalization
 9.5 Direct histogram specification
 9.6 Other histogram modification techniques
 9.7 Tutorial 9.1: Image histograms
 9.8 Tutorial 9.2: Histogram equalization and specification
 9.9 Tutorial 9.3: Other histogram modification techniques
 What have we learned?
 Learn more about it
 9.10 Problems

Chapter 10: Neighborhood Processing
 What will We Learn?
 10.1 Neighborhood Processing
 10.2 Convolution and Correlation
 10.3 Image Smoothing (LowPass Filters)
 10.4 Image Sharpening (HighPass Filters)
 10.5 Region of Interest Processing
 10.6 Combining Spatial Enhancement Methods
 10.7 Tutorial 10.1: Convolution and Correlation
 10.8 Tutorial 10.2: Smoothing Filters in the Spatial Domain
 10.9 Tutorial 10.3: Sharpening Filters in the Spatial Domain
 What have we learned?
 Learn more about it
 10.10 Problems

Chapter 11: FrequencyDomain Filtering
 11.1 Introduction
 11.2 Fourier Transform: the mathematical foundation
 11.3 Lowpass filtering
 11.4 Highpass filtering
 11.5 Tutorial 11.1: 2D Fourier Transform
 11.6 Tutorial 11.2: Lowpass filters in the frequency domain
 11.7 Tutorial 11.3: Highpass filters in the frequency domain
 What have we learned?
 Learn more about it
 11.8 Problems

Chapter 12: Image Restoration
 What will We Learn?
 12.1 Modeling of the Image Degradation and Restoration Problem
 12.2 Noise and Noise Models
 12.3 Noise Reduction Using SpatialDomain Techniques
 12.4 Noise Reduction Using FrequencyDomain Techniques
 12.5 Image deblurring techniques
 12.6 Tutorial 12.1: Noise Reduction Using SpatialDomain Techniques
 12.7 Problems

Chapter 13: Morphological Image Processing
 What will We Learn?
 13.1 Introduction
 13.2 Fundamental concepts and operations
 13.3 Dilation and erosion
 13.4 Compound operations
 13.5 Morphological filtering
 13.6 Basic morphological algorithms
 13.7 Grayscale morphology
 13.8 Tutorial 13.1: Binary morphological image processing
 13.9 Tutorial 13.2: Basic morphological algorithms
 What have we learned?
 Learn more about it
 13.10 Problems
 Chapter 14: Edge Detection
 Chapter 15: Image Segmentation

Chapter 16: Color Image Processing
 What Will we Learn?
 16.1 The Psychophysics of Color
 16.2 Color Models
 16.3 Representation of color images in MATLAB
 16.4 Pseudocolor Image Processing
 16.5 FullColor Image Processing
 16.6 Tutorial 16.1: Pseudocolor Image Processing
 16.7 Tutorial 16.2: FullColor Image Processing
 What have We Learned?
 Learn More About It
 On the Web
 16.8 Problems
 Chapter 17: Image Compression and Coding

Chapter 18: Feature Extraction and Representation
 What will we learn?
 18.1 Introduction
 18.2 Feature vectors and vector spaces
 18.3 Binary object features
 18.4 Boundary descriptors
 18.5 Histogrambased (statistical) features
 18.6 Texture features
 18.7 Tutorial 18.1: Feature extraction and representation
 What have we learned?
 Learn more about it
 18.8 Problems
 Chapter 19: Visual Pattern Recognition

Part II: Video Processing

Chapter 20: Video Fundamentals
 What Will We Learn?
 20.1 Basic Concepts and Terminology
 20.2 Monochrome Analog Video
 20.3 Color in Video
 20.4 Analog Video Standards
 20.5 Digital Video Basics
 20.6 AnalogtoDigital Conversion
 20.7 Color Representation and Chroma Subsampling
 20.8 Digital Video Formats and Standards
 20.9 Video Compression Techniques and Standards
 20.10 Video processing in MATLAB
 20.11 Tutorial 20.1: Basic Digital Video Manipulation in MATLAB
 20.12 Tutorial 20.2: Working with YUV video data
 What Have We Learned?
 Learn More About It
 On the Web
 20.13 Problems

Chapter 21: Video Sampling Rate and Standards Conversion
 What Will We Learn?
 21.1 Video Sampling
 21.2 Sampling Rate Conversion
 21.3 Standards Conversion
 21.4 Tutorial 21.1: Line DownConversion
 21.5 Tutorial 21.2: Deinterlacing
 21.6 Tutorial 21.3: NTSC to PAL Conversion
 21.7 Tutorial 21.4: 3:2 PullDown
 What Have We learned?
 Learn More About It
 21.8 Problems

Chapter 22: Digital Video Processing Techniques and Applications
 What Will We Learn?
 22.1 Fundamentals of Motion Estimation and Motion Compensation
 22.2 General Methodologies in Motion Estimation
 22.3 Motion Estimation Algorithms
 22.4 Video Enhancement and Noise Reduction
 22.5 Case Study: Object Segmentation and Tracking in the Presence of Complex Background
 22.6 Tutorial 22.1: Blockbased Motion Estimation
 22.7 Tutorial 22.2: Intraframe and Interframe Filtering Techniques
 What Have We Learned?
 Learn More About It
 22.8 Problems

Chapter 20: Video Fundamentals
 Appendix A: Human Visual Perception
 Appendix B: Gui Development
 References
 Index
Product information
 Title: Practical Image and Video Processing Using MATLAB®
 Author(s):
 Release date: September 2011
 Publisher(s): WileyIEEE Press
 ISBN: 9780470048153
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