Kenneth R. Castleman, Perceptive Scientific Instruments, Inc.

Published August, 1995 by Prentice Hall Engineering/Science/Mathematics

Copyright 1996, 667 pp.
Cloth
ISBN 0-13-211467-4

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    Image Processing-Electrical Engineering

    Image Processing-Computer Science

Ideal for those who do not possess an advanced background in electrical engineering, this broad introduction to the fundamental concepts of digital imaging shows how the various techniques can be applied to solve real-world problems (e.g., in biology, astronomy, forensics, etc.). It helps students develop the insight required to use the tools of digital imaging to solve new problems.




treats digital image processing as a tool for solving practical problems, rather than as a discipline in itself.
concentrates on the fundamental techniques that have proven to be the most important and useful in solving real-world problems.
develops the techniques in sequential order of mathematical complexity.
presents techniques in a straightforward manner, considering for each technique:

• the theoretical background required for understanding the technique.
• a description of the technique and discussion of its applications, limitations, and performance.
• an illustration and worked-example of its use.

stresses consistent definitions throughout.

• NEW—provides a summary of mathematical background and a comprehensive glossary.

NEW—adds discussions of color, image compression, user interfaces, software development project management, Wavelet Transforms.
NEW—expands discussions of analysis of digital imaging systems performance, optics, pattern recognition, image recording and display, CCD cameras and 3-D imaging.
NEW—contains Summary of Important Points, Problems and Class Project suggestions at the end of each chapter.

• Problems focus on the application of the tools to real situations, and provide insight into when different techniques are useful, and when they might fail.
  
  

I.

1. Images and Digital Processing.
2. Digitizing Images.
3. Digital Image Display.
4. Image-Processing Software.
5. The Gray-Level Histogram.
6. Point Operations.
7. Algebraic Operations.
8. Geometric Operations.

II.

9. Linear Systems Theory.
10. The Fourier Transform.
11. Filter Design.
12. Processing Sampled Data.
13. Discrete Image Transforms.
14. Wavelet Transforms.
15. Optics and System Analysis.

III.

16. Image Restoration.
17. Image Compression.
18. Pattern Recognition: Image Segmentation.
19. Pattern Recognition: Object Measurement.
20. Pattern Recognition: Classification and Estimation.
21. Color and Multispectral Image Processing.
22. Three-Dimensional Image Processing.

APPENDICES.

A1. Glossary of Image Processing Terms.
A2. Bibliography.
A3. Mathematical Background.
Index.

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