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The Image Processing Handbook, Seventh Edition, by John C. Russ, F. Brent Neal
Download Ebook The Image Processing Handbook, Seventh Edition, by John C. Russ, F. Brent Neal
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Consistently rated as the best overall introduction to computer-based image processing, The Image Processing Handbook covers two-dimensional (2D) and three-dimensional (3D) imaging techniques, image printing and storage methods, image processing algorithms, image and feature measurement, quantitative image measurement analysis, and more.
Incorporating image processing and analysis examples at all scales, from nano- to astro-, this Seventh Edition:
- Features a greater range of computationally intensive algorithms than previous versions
- Provides better organization, more quantitative results, and new material on recent developments
- Includes completely rewritten chapters on 3D imaging and a thoroughly revamped chapter on statistical analysis
- Contains more than 1700 references to theory, methods, and applications in a wide variety of disciplines
- Presents 500+ entirely new figures and images, with more than two-thirds appearing in color
The Image Processing Handbook, Seventh Edition delivers an accessible and up-to-date treatment of image processing, offering broad coverage and comparison of algorithms, approaches, and outcomes.
- Sales Rank: #1428870 in Books
- Published on: 2015-11-11
- Original language: English
- Number of items: 1
- Dimensions: 10.20" h x 1.90" w x 7.60" l, .0 pounds
- Binding: Hardcover
- 1053 pages
Review
Praise for the Previous Edition
"… a welcome addition to any reference shelf. Experienced researchers as well as novices will turn to it often to learn about imaging, while for students it provides a gentle yet thorough introduction―appropriate at either the undergraduate or graduate level―to a set of techniques that are used in as many wide-ranging disciplines as microscopy itself. Highly recommended, the book is extremely readable and captures the style of an experienced, knowledgeable teacher."
―Lou Ross, Electron Microscopy Core, University of Missouri, Columbia, USA, from Microscopy and Microanalysis, Volume 17, Issue 05
About the Author
John C. Russ has used image processing and analysis as a principal tool for understanding and characterizing the structure and function of materials throughout his more than 50-year career as a scientist and educator. Much of Russ' research work has been concerned with the microstructure and surface topography of metals and ceramics. He has received funding for his research from government agencies and from industry. Teaching the principles and methods involved to several thousand students―in addition to consulting for many industrial clients―has further broadened Dr. Russ’ experience and the scope of applications for image processing and analysis. He continues to write and consult for a variety of companies (and to provide expert testimony in criminal and civil cases). He also still teaches image processing and analysis workshops worldwide and reviews publications and funding proposals.
F. Brent Neal is a scientist and industrial researcher with Milliken Research Corporation, where he currently leads the central materials characterization and analytical chemistry facility. In this role, he leads efforts in technology and product development through deep understanding of materials performance. He has three patents issued or pending based on his work in polymer-matrix composites. Prior to his tenure at Milliken Research Corporation, he consulted and developed bespoke software for quantitative image analysis. He received his Ph.D in solid-state physics from Louisiana State University in 2002. Over the course of his career, he has measured and analyzed images from many different fields and his experience in materials characterization and measurement has been applied everywhere from the lab bench to manufacturing plants.
Most helpful customer reviews
0 of 0 people found the following review helpful.
Highly recommended
By Chia-Hsing L.
Very clearly summarizing versatile image processing algorithms
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