Digital image processing: an algorithmic approach with matlab
- Boca Raton CRC Press
- xx, 286p. pbk
- Chapman & Hall/Crc Textbook In Computing .
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
Introduction Image Compression–Decompression Steps Classifying Image Data Bit Allocation Quantization Entropy Coding JPEG Compression Algorithmic Account MATLAB Code
Edge Detection
Introduction The Sobel Operator The Prewitt Operator The Canny Operator The Compass Operator (Edge Template Matching) The Zero-Crossing Detector Line Detection The Unsharp Filter Algorithmic Account MATLAB Code
Introduction Watermarking Methodology Basic Principle of Watermarking Problems Associated with Watermarking Algorithmic Account MATLAB Code
Image Classification and Segmentation
Introduction General Idea of Classification Common Intensity-Connected Pixel: Naïve Classifier Nearest Neighbor Classifier Unsupervised Classification Algorithmic Account MATLAB Code