Preface – Fundamentals of Digital Image Processing


Digital image processing is a popular subject evolving continuously. This book covers topics like image enhancement, transformation, segmentation, compression, restorations, image representation and description, and recognition and interpretation in detail. The text is an outcome of our teaching experience and research findings at the Department of Computer Science and Engineering in Government College of Technology, Coimbatore and provides a basic foundation for various topics in digital image processing. In general, the field of digital image processing requires sound theoretical knowledge and extensive experimental work involving software simulation and testing with large sets of sample images. The book has been designed to meet these requirements and provides hands-on experience to students in implementing various algorithms for image processing. All the sample algorithms given in this book are implemented in C++. The text is intended primarily for UG/PG level students in computer science and engineering, information technology, and electronics and communication engineering.

The book is organized as follows:

Chapter 1 introduces the set of core ideas that are used throughout the rest of the text. Motivated by a typical application, it discusses the fundamentals of digital image processing. Display of images on the computer monitor is explained with the help of a C++ program.

Chapter 2 introduces coordinate systems, which are used to represent the images. The relationship among pixels is widely used in many applications, and is described in detail in this chapter.

Chapter 3 covers the various image transforms exhaustively. Fast Fourier (FFT) and Discrete Cosine Transforms (DCT) are the two most popular transforms. Usage of the former in recognition applications and the latter in image compression is discussed.

Chapter 4 deals with image enhancement techniques. The various spatial and frequency domain techniques of image enhancement are well explained in this chapter. To simulate various enhancement algorithms, C++ sample programs are developed for students. C++ programs are provided for image histogram equalization technique, low pass and high pass filters, so as to help students get a better understanding on these topics.

Chapter 5 covers the lossy and lossless image compression techniques. In addition to these, a few neural network approaches for image compression are also introduced.

Chapter 6 deals with the segmentation concepts. Various segmentation approaches using the concepts of thresholding, graph, and region splitting and merging are explained in this chapter.

Chapter 7 explains the various approaches of restoration of degraded images. Restoration is a technique to remove the noise present in the images. The algebraic approach, constrained and unconstrained approaches, and interactive approaches for restoration are included in this chapter.

Chapter 8 discusses the various representation and description schemes. Various schemes like run-length code, quadfree, and skeletons using internal characteristics are also explained.

Chapter 9 deals with statistical and neural network based classifiers for recognition, and semantic networks for interpretation. In addition to these topics image knowledge base, semantic net, and predicate logic are well explained in this chapter.


S. Annadurai
R. Shanmugalakshmi