Features and topics:
- Practical examples and carefully constructed chapter-ending exercises drawn from the authors' years of experience teaching this material
- 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 (and rapid prototyping of new) applications
- Uses ImageJ, the image processing system developed, maintained, and freely distributed by the U.S. National Institutes of Health (NIH)
- Provides a supplementary website with the complete Java source code, test images, and corrections - www.imagingbook.com
- Additional presentation tools for instructors including a complete set of figures, tables, and mathematical elements
This concise, yet comprehensive and reader-friendly text is ideal for undergraduates studying foundation courses, as well as ideal for those seeking to expand their knowledge via self-study.
Wilhelm Burger, Ph.D., is the director of the Digital Media degree programs at the UpperAustria University of Applied Sciences at Hagenberg. Mark J. Burge, Ph.D., is a senior principal in the Center for National Security and Intelligence at Noblis in Washington, D.C.
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"This text is the second of three volumes by Burger and Burge to provide an algorithmic introduction to digital image processing. ... This textbook is for academicians who want a mathematical or theoretical foundation that underlies the methods used, as well as for engineers who are interested in practical implementations of the most important algorithms. The volume is a very nice extension to the material and a worthwhile read." (Minette Carl, ACM Computing Reviews, August, 2009)
"This is the second textbook from authors three-book series for graduate and post-graduate courses covering digital image processing techniques; earlier the material appeared in one comprehensive volume Digital Image Processing: An Algorithmic Introduction using Java. This volume covers regions in binary images, curve and corner detecting, color spaces and quantization, transformations ... and comparing/matching of images. The presentation is very algorithmic and expects hands-on experimentation with presented notions and algorithms, every chapter ends with exercises ... ." (Jaak Henno, Zentralblatt MATH, Vol. 1185, 2010)