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Introduction to digital imaging covering core techniques of image capture and the display of monochrome and color images. Basic tools required to describe sampling and image display on real devices are presented within a powerful mathematical framework. Starting with an overview of digital imaging, mathematical representation, and the elementary display of images, the topics progressively move to quantization, spatial sampling, photometry and colorimetry, and color sampling, and conclude with the estimation of image model parameters, and image restoration. The characterization of input and output devices is also covered. The reader will learn the processes used to generate accurate images, and appreciate the mathematical basis required to test and evaluate new devices. Contains illustrations, real-world examples, and end-of-chapter homework problems. Suitable for advanced undergraduate and graduate courses in digital imaging in electrical engineering and computer science departments. Also invaluable for practitioners in the industry. Instructor resources are available online at www.cambridge.org/9780521868532.Read more
- Covers image capture and the display of monochrome and color images - core topics that are often overlooked
- Uses real-world applications to balance the mathematical descriptions of real problems
- Instructor-only solutions, MATLAB scripts, and reference data for problems are available online at www.cambridge.org/9780521868532
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- Date Published: October 2008
- format: Hardback
- isbn: 9780521868532
- length: 550 pages
- dimensions: 253 x 180 x 30 mm
- weight: 1.6kg
- contains: 240 b/w illus. 35 colour illus.
- availability: Available
Table of Contents
2. Mathematical representation
3. Elementary display of images
5. Frequency domain representation
6. Spatial sampling
7. Image characteristics
8. Photometry and colorimetry
9. Color sampling
10. Image input devices
11. Image output devices and methods
12. Characterization of devices
13. Estimation of image model parameters
14. Image restoration
Appendices: A. Generalized functions (singularity operators)
B. Digital image manipulation and matrix representation
C. Stochastic images
D. Multidimensional look-up-tables
E. Psychovisual properties.
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