Digital image processing : an algorithmic introduction using Java
著者
書誌事項
Digital image processing : an algorithmic introduction using Java
（Texts in computer science）
Springer, c2016
2nd ed
大学図書館所蔵 全2件
注記
Includes bibliographical references (p. 777-789) and index
内容説明・目次
内容説明
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.
The text is supported by practical examples and carefully constructed chapter-ending exercises drawn from the authors' years of teaching experience, including easily adaptable Java code and completely worked out examples. Source code, test images and additional instructor materials are also provided at an associated website. Digital Image Processing is the definitive textbook for students, researchers, and professionals in search of critical analysis and modern implementations of the most important algorithms in the field, and is also eminently suitable for self-study.
目次
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.
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