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Design for Embedded Image Processing on FPGAs. Second Edition
Title: Design for Embedded Image Processing on FPGAs. Second Edition
Author: Donald G. Bailey
Year: 2024
Publisher: Wiley
English language
Format: pdf (true)
Pages: 497
Size: 10.2 MB
Beginning with an overview of image processing and its core principles, this book discusses specific design and computation techniques, with a smooth progression from the foundations of the field to its advanced principles.
Readers of the second edition of Design for Embedded Image Processing on FPGAs will also find:
Detailed discussion of image processing techniques including point operations, histogram operations, linear transformations, and more.
New chapters covering Deep Learning algorithms and Image and Video Coding.
Example applications throughout to ground principles and demonstrate techniques.
New chapters covering Deep Learning algorithms and Image and Video Coding.
Example applications throughout to ground principles and demonstrate techniques.
Design for Embedded Image Processing on FPGAs is ideal for engineers and academics working in the field of Image Processing, as well as graduate students studying Embedded Systems Engineering, Image Processing, Digital Design, and related fields.
Contents:
1. Image Processing
2. Field-programmable Gate Arrays
3. Design Process
4. Design Constraints
5. Computational Techniques
6. Interfacing
7. Point Operations
8. Histogram Operations
9. Local Filters
10. Geometric Transformations
11. Linear Transforms
12. Image and Video Coding
13. Blob Detection and Labelling
14. Machine Learning
15. Example Applications
2. Field-programmable Gate Arrays
3. Design Process
4. Design Constraints
5. Computational Techniques
6. Interfacing
7. Point Operations
8. Histogram Operations
9. Local Filters
10. Geometric Transformations
11. Linear Transforms
12. Image and Video Coding
13. Blob Detection and Labelling
14. Machine Learning
15. Example Applications
Download : Donald G. Bailey. Design for Embedded Image Processing on FPGAs. Second Edition
~ Turbobit
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