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.

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.

Description based on publisher-supplied MARC data.