Signal processing using optics : fundamentals, devices, architectures, and applications

著者

書誌事項

Signal processing using optics : fundamentals, devices, architectures, and applications

Bradley G. Boone

（The Johns Hopkins University/Applied Physics Laboratory series in science and engineering）

Oxford University Press, 1998

  • : cloth

大学図書館所蔵 件 / 全21件

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注記

Includes bibliographical references and index

内容説明・目次

内容説明

This textbook covers the basic aspects of otical signal processing at an introductory level, yet it should help the student bridge the gap to current technical literature. It is intnded for senior-level undergraduate or first-year graduate students in the electrical engineering or applied physics as well as practicing engineers and scientists. Although the student or professional should have some exposure to one-dimensional signal processing, optics, and imaging to make the book self-contained and the necessary background information readily accessible. The text aim is to provide the student with insight on the underlying mathematical and physical principles, practical understanding of component technology and performance, a grasp of system design and analysis, and familiarity with architectures for selected but representative applications. Problem exercise, selected hints and solution, extensive reference, and MATLAB based modeling ansd simulation tools are included to support the student's exploration of applications and to direct their learning towards the current technical literature. Numerous architectural diagrams are provided to assist in the understanding and visualization of important concepts and their implementation.

目次

  • Introduction
  • 1. Two-dimensional linear systems
  • 1.1 Fundamental properties
  • 1.2 Linear superposition
  • 1.3 Convolution and correlation
  • 1.4 Two-dimensional Fourier transforms and properties
  • 1.5 Rectangular and polar form
  • 1.6 Linear coordinate transformation and Fourier theorem
  • 1.7 Examples of magnification and rotation
  • 1.8 Two dimensional impulse fuctions: properties and Fourier transforms
  • 1.9 Elementary images and their Fourier properties
  • 2. Stochastic processes and nonlinear systems
  • 2.1 Basic concepts of stachsatic processes
  • 2.2 Fundamental probability density functions
  • 2.3 Matched filter derivation and properties of correlation
  • 2.4 Nonlinear transformations and operations
  • 2.5 Mixing and modulation
  • 3. Mathematical transforms used in optical signal processing
  • 3.1 Overview
  • 3.2 Fresnel transform
  • 3.3 Hilbert transform
  • 3.4 Radon transform
  • 3.5 Mellin transform
  • 3.6 Wavelet transform
  • 4. Fundamental properties of light and geometric optics
  • 4.1 Overview
  • 4.2 Fundamental scalar and vector properties of light
  • 4.3 Polarization
  • 4.4 Rectilinear glass structures and their properties
  • 4.5 Simple lenses and lens combinations
  • 5. Summary of physical optics
  • 5.1 Overview
  • 5.2 Coherence and interference
  • 5.3 Scalar diffraction theory
  • 5.4 Fraunhofer diffraction
  • 5.5 Fresnel diffraction
  • 6. Fourier transform and imaging properties of optical systems
  • 6,1 Overview
  • 6.2 Effects of lens on a wavefront
  • 6.3 Imaging property of lenses
  • 6.5 Linear system properties of imaging systems
  • 6.6 Pint spread function
  • 6.7 Optical trasnfer function
  • 6.9 Signal processing analogies for optics
  • 7. Light sources and detectors
  • 7.1 Overview
  • 7.2 Laser principles of operations
  • 7.3 Laser diode arrays
  • 7.4 Output light detectors
  • 7.5 Single detectors
  • 7.6 Linear and matrix arrays
  • 7.7 Optical signal processing requirements
  • 8. Spatial light modulators
  • 8.1 Acousto-optic Bragg cells
  • 8.3 Liquid crystal spatial light modulators
  • 8.4 Magneto-optic spatial light modulator
  • 8.5 Other spatial light modulators
  • 9. Optical spectrum analysis and correlation
  • 9.1 Overview
  • 9.2 Time and space integrating architectures
  • 9.3 Coherent and incoherent architecture
  • 9.4 Spectrum analysis
  • 9.5 Space integrating spectrum analyzer
  • 9.6 Time integrating spectrum analyzer
  • 9.7 Correlation
  • 9. 8 Incoherent optical correlator architectures
  • 9.9 Coherent optical correlator architectures
  • 10. Image and matched spatial filtering
  • 10.1 Overview
  • 10.2 VanderLugt filter
  • 10.3 Image spatial filtering
  • 10.4 Matched spatial filter and binary phase-only correlators
  • 10.5 Techniques for circumvention geometric distortions
  • 10.6 Spatial multiplexing
  • 10.7 Distortion invariant transformations
  • 10.8 Angular correlation
  • 11. Radar signal processing applications
  • 11.1 Overview
  • 11.2 Radar signal processing
  • 11.3 Ambiguity function processing
  • 11.4 Synthetic aperture radar
  • 12. Pattern recognition applications
  • 12.1 Overview
  • 12.2 Feature extraction
  • 12. 3 Optical vector-matrix multiplication
  • 12.4 Optical neural networks
  • Appendix A: Mathematical Tables
  • Appendix B: Annotated Bibliography
  • Appendix C: Software for Modeling and Visualization
  • Appendix D: Hints and Solutions to selected problems
  • References
  • Index

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