This modern, self-contained textbook provides an accessible introduction to the field from the perspective of a practicing programmer, supporting a detailed presentation of the fundamental concepts and techniques with practical exercises and fully worked out implementation examples. This much-anticipated new edition of the definitive textbook on Digital Image Processing has been completely revised and expanded with new content and improved teaching material.

Topics and features:

• Contains new chapters on automatic thresholding, filters and edge detection for color images, edge-preserving smoothing filters, non-rigid image matching, and Fourier shape descriptors.
• Includes exercises at the end of every chapter, and provides additional supplementary material at an associated website.
• Uses ImageJ for all examples, a widely used open source imaging system that can run on all major platforms and be easily ported to other programming languages.
• Describes each solution in a stepwise manner in mathematical form, as abstract pseudocode algorithms, and as complete Java programs.
• Presents suggested outlines for a one- or two-semester course in the preface.

Advanced undergraduate and graduate students will find this comprehensive and example-rich textbook will serve as the ideal introduction to digital image processing. It will also prove invaluable to researchers and professionals seeking a practically focused self-study primer.

Dr. Wilhelm Burger is a faculty member of the University of Applied Sciences Upper Austria, Hagenberg, where he serves as Director of the Digital Media degree programs at the School of Informatics, Communications and Media.

Dr. Mark J. Burge is a scientist at the non-profit organization Noblis in Falls Church, VA, USA. His other publications include the Handbook of Iris Recognition.

This revised and expanded new edition of an internationally successful classic presents an accessible introduction to the key methods in digital image processing for both practitioners and teachers. Emphasis is placed on practical application, presenting precise algorithmic descriptions in an unusually high level of detail, while highlighting direct connections between the mathematical foundations and concrete implementation.

Digital Images.- ImageJ.- Histograms and Image Statistics.- Point Operations.- Filters.- Edges and Contours.- Corner Detection.- Finding Simple Curves: The Hough Transform.- Morphological Filters.- Regions in Binary Images.- Automatic Thresholding.- Color Images.- Color Quantization.- Colorimetric Color Spaces.- Filters for Color Images.- Edge Detection in Color Images.- Edge-Preserving Smoothing Filters.- Introduction to Spectral Techniques.- The Discrete Fourier Transform in 2D.- The Discrete Cosine Transform (DCT).- Geometric Operations.- Pixel Interpolation.- Image Matching and Registration.- Non-Rigid Image Matching.- Scale-Invariant Feature Transform (SIFT).- Fourier Shape Descriptors.- Appendix A: Mathematical Symbols and Notation.- Appendix B: Linear Algebra.- Appendix C: Calculus.- Appendix D: Statistical Prerequisites.- Appendix E: Gaussian Filters.- Appendix F: JavaNotes.