Digital Image Processing with C++: Implementing Reference Algorithms with the CImg Library 1st Edition
by David Tschumperle(Author), Christophe Tilmant(Author), Vincent Barra(Author)
Publisher Finelybook 出版社: CRC Press; 1st edition (March 23, 2023)
Language 语言: English
Hardcover: 312 pages
ISBN-10: 103234752X
ISBN-13: 9781032347523
Book Description
Digital Image Processing with C++ presents the theory of digital image processing, and implementations of algorithms using a dedicated library. Processing a digital image means transforming its content (denoising, stylizing, etc.), or extracting information to solve a given problem (object recognition, measurement, motion estimation, etc.). This book presents the mathematical theories underlying digital image processing, as well as their practical implementation through examples of algorithms implemented in the C++ language, using the free and easy-to-use CImg library.
Chapters cover in a broad way the field of digital image processing and proposes practical and functional implementations of each method theoretically described. The main topics covered include filtering in spatial and frequency domains, mathematical morphology, feature extraction and applications to segmentation, motion estimation, multispectral image processing and 3D visualization.
Students or developers wishing to discover or specialize in this discipline, teachers and researchers wishing to quickly prototype new algorithms, or develop courses, will all find in this book material to discover image processing or deepen their knowledge in this field.
Digital Image Processing with C++: Implementing Reference Algorithms with the CImg Library
未经允许不得转载:finelybook » Digital Image Processing with C++: Implementing Reference Algorithms with the CImg Library
相关推荐
- Building Decentralized Blockchain Applications: Learn how to use blockchain as the foundation for Next-Gen Apps, 2nd Edition
- Data Science Essentials with R: Learn with focus on data manipulation, visualization, and machine learning
- Variational Methods for Machine Learning with Applications to Deep Networks
- Ultimate Python for Fintech Solutions: Build Modern Financial Applications and Fintech Solutions Using Finance Packages and Blockchain with Python
finelybook
