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№ на артикул:
148198724
Texts in Computer Science Digital Image Processing: An Algorithmic Introduction, (Hardcover)
92% of respondents would recommend this to a friend
№ на артикул:
148198724
€ 93
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This comprehensive and example-rich textbook serves as the ideal introduction to digital image processing for advanced undergraduate and graduate students.
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What Stands Out
Comprehensive Coverage
Offers an extensive overview of digital image processing techniques, making complex algorithms accessible for beginners and experts alike, enhancing the reader's ability to apply knowledge practically.
Algorithmic Focus
Emphasizes algorithmic approaches, providing readers with step-by-step guides and real-world applications, ensuring they can implement effective solutions to common image processing challenges.
User-Friendly Format
Designed as a hardcover edition, it ensures durability and easy reference, catering to students and professionals who seek a reliable resource for continuous learning and practical application.
Информация за продукта
| Book format | Hardcover |
| Fiction/nonfiction | Non-Fiction |
| Genre | Computing & Internet |
| Publication date | July, 2022 |
| Pages | 945 |
| Reading level | Grade 1, Grade 10, Grade 11, Grade 12, Grade 2, Grade 3, Grade 4, Grade 5, Grade 6, Grade 7, Grade 8, Grade 9, Kindergarten, Preschool |
| Subgenre | Software Development & Engineering |
| Series title | Texts in Computer Science |
| Number in series | 3 |
| Edition | 3rd third 2022 Edition |
| Publisher | Springer International Publishing |
| Original languages | English |
| Language | English |
| Edu focus | Technology |
| Educational level | College |
| Is collectible | N |
| Binding type | Case Binding |
| Number of discs | 1 |
| Retail packaging | Single Piece |
| Assembled product height | 10 in |
| Assembled product weight | 5.19 lb (2.35 kg) |
| Bisac subject heading | Computers |
Who Should Buy?
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Students of CS
Ideal for computer science students focusing on digital image processing methodologies and algorithm development techniques.
-
Professionals in Tech
Useful for tech professionals looking to enhance their knowledge in image processing algorithms and applications in real-world scenarios.
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Researchers
Beneficial for researchers conducting studies or projects related to algorithmic approaches in digital image processing.
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Casual Readers
Not suitable for casual readers seeking light content or general knowledge about digital imaging without technical details.
ОПИСАНИЕ НА ПРОДУКТА
Texts in Computer Science Digital Image Processing: An Algorithmic Introduction, (Hardcover)
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Wilhelm Burger Ages 9-12 Kids' Books Editorial Review
Texts in Computer Science Digital Image Processing: An Algorithmic Introduction is a comprehensive hardcover book published in July 2022, tailored for those delving into the world of digital image processing. This third edition spans 945 pages, providing valuable insights into software development and engineering from an educational perspective. Targeted primarily towards college-level readers, it covers a range of reading levels, making it accessible for various learners. The book is published by Springer International Publishing, ensuring a solid academic reputation. Overall, it's a well-structured resource for anyone interested in mastering this crucial aspect of computing.
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Професионалисти
- Comprehensive coverage of digital image processing
- Suitable for various educational levels
- High-quality hardcover format
- Published by a reputable publisher
- In-depth insights into software engineering
минуси
- Weight may be cumbersome for some readers
Product Price History
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€ 93
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Характеристики и предимства
- Modern, self-contained textbook on Digital Image Processing.
- Completely revised 3rd edition with new content and improved illustrations.
- Includes exercises and supplementary materials available online.
- Uses ImageJ for practical examples on all major platforms.
- Describes solutions in mathematical form, pseudocode algorithms, and complete Java programs.
- Ideal for advanced students, researchers, and professionals for self-study.
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