Avoiding heavy mathematics and lengthy programming details, Digital Image Processing: An Algorithmic Approach with MATLAB® presents an easy methodology for learning the fundamentals of image processing. The book applies the algorithms using MATLAB®, without bogging down students with syntactical and debugging issues.
One chapter can typically be completed per week, with each chapter divided into three sections. The first section presents theoretical topics in a very simple and basic style with generic language and mathematics. The second section explains the theoretical concepts using flowcharts to streamline the concepts and to form a foundation for students to code in any programming language. The final section supplies MATLAB codes for reproducing the figures presented in the chapter. Programming-based exercises at the end of each chapter facilitate the learning of underlying concepts through practice.
This textbook equips undergraduate students in computer engineering and science with an essential understanding of digital image processing. It will also help them comprehend more advanced topics and sophisticated mathematical material in later courses. A color insert is included in the text while various instructor resources are available on the author’s website.
Table of Contents
Introduction to Image Processing and the MATLAB Environment
Digital Image Definitions: Theoretical Account
Image Acquisition, Types, and File I/O
Image Types and File I/O
Basics of Color Images
Other Color Spaces
Affine and Logical Operations, Distortions, and Noise in Images
Noise in Images
Distortions in Images
Discrete Fourier Transform (DFT) in 2D
Spatial and Frequency Domain Filter Design
Spatial Domain Filter Design
Frequency-Based Filter Design
Image Restoration and Blind Deconvolution
Image Compression–Decompression Steps
Classifying Image Data
The Sobel Operator
The Prewitt Operator
The Canny Operator
The Compass Operator (Edge Template Matching)
The Zero-Crossing Detector
The Unsharp Filter
Binary Image Processing
Skeletonization/Medial Axis Transform
Image Encryption and Watermarking
Basic Principle of Watermarking
Problems Associated with Watermarking
Image Classification and Segmentation
General Idea of Classification
Common Intensity-Connected Pixel: Naïve Classifier
Nearest Neighbor Classifier
Image-Based Object Tracking
Temporal Difference between Frames
Face Recognition Approaches
Vector Representation of Images
Soft Computing in Image Processing
Fuzzy Logic in Image Processing
A Summary and Exercises appear at the end of each chapter.
Uvais Qidwai is an assistant professor in the computer science and engineering department at Qatar University in Doha.
C.H. Chen is chancellor professor in electrical and computer engineering at the University of Massachusetts in North Dartmouth.
"…This book covers a reasonably large area of the subject for there to be something for most readers. …"
—I-Programmer, January 2010