This textbook is the third of three volumes which provide a modern, algorithmic introduction to digital image processing, designed to be used both by learners desiring a firm foundation on which to build, and practitioners in search of critical analysis and concrete implementations of the most important techniques. This volume builds upon the introductory material presented in the first two volumes with additional key concepts and methods in image processing. Features: practical examples and carefully constructed chapter-ending exercises; real implementations, concise mathematical notation, and precise algorithmic descriptions designed for programmers and practitioners; easily adaptable Java code and completely worked-out examples for easy inclusion in existing applications; uses ImageJ; provides a supplementary website with the complete Java source code, test images, and corrections; additional presentation tools for instructors including a complete set of figures, tables, and mathematical elements.

Introduction.- Automatic Thresholding.- Filters for Color Images.- Edge Detection in Color Images.- Edge-Preserving Smoothing Filters.- Fourier Shape Descriptors.- SIFT-Scale-Invariant Local Features.- Mathematical Symbols and Notation.- Vector Algebra and Calculus.- Statistical Prerequisites.- Gaussian Filters.- Color Space Transformations.