A Concise Introduction to Image Processing using C++
Language: English
Published by Taylor & Francis Inc Nov 2008, 2008
Series: Book 21 of 34 - Chapman & Hall/CRC Numerical Analysis and Scientific Computing
- Hardcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
AbeBooks seller since August 14, 2006
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Add to basketItem description from seller
Neuware - Written by experts in fractal-based image and video compression, this book strengthens readers' knowledge of fundamentals principles in image acquisition, conservation, processing, and manipulation, improving their ability to apply these techniques in real-world problems. The book begins with coverage of representation, moves on to communications and processing, and concludes with discussions of processing techniques based on image representations and transformations developed in earlier chapters. Suitable as a text for any course on image processing, the book can also be used for self-study by researchers. The accompanying CD-ROM contains code for all algorithms.
Seller Inventory # 9781584888970
- Title
- A Concise Introduction to Image Processing using C++
- Author
- Meiqing (College of Mathematics and Computer Science Wang
- Publisher
- Taylor & Francis Inc Nov 2008
- Publication year
- 2008
- Condition
- Neu
- Binding
- Buch
- Language
- English
- ISBN 10
- 1584888970
- ISBN 13
- 9781584888970
- Item weight
- 554 grams
- Dimensions
- 245x162x17 mm
- Series
- Book 21 of 34: Chapman & Hall/CRC Numerical Analysis and Scientific Computing
Image recognition has become an increasingly dynamic field with new and emerging civil and military applications in security, exploration, and robotics. Written by experts in fractal-based image and video compression, A Concise Introduction to Image Processing using C++ strengthens your knowledge of fundamentals principles in image acquisition, conservation, processing, and manipulation, allowing you to easily apply these techniques in real-world problems.
The book presents state-of-the-art image processing methodology, including current industrial practices for image compression, image de-noising methods based on partial differential equations (PDEs), and new image compression methods, such as fractal image compression and wavelet compression. It begins with coverage of representation, and then moves on to communications and processing. It concludes with discussions of processing techniques based on image representations and transformations developed in earlier chapters. The accompanying downloadable resources contain code for all algorithms.
Suitable as a text for any course on image processing, the book can also be used as a self-study resource for researchers who need a concise and clear view of current image processing methods and coding examples. The authors introduce mathematical concepts with rigor suitable for readers with some background in calculus, algebra, geometry, and PDEs. All algorithms described are illustrated with code implementation and many images compare the results of different methods. The inclusion of C++ implementation code for each algorithm described enables students and practitioners to build up their own analysis tool.
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