Signal Processing Using Optics

Description

Signal Processing Using Optics covers the fundamental aspects of optical signal processing at an introductory level and also discusses more applied topics, helping students and professionals bridge the gap to the current technical literature. Although readers are expected to have previous knowledge of one-dimensional signals and systems and optics beyond general physics, this self-contained text reviews the essentials of signal processing, optics, and imaging to make necessary background information readily available. It continues on with coverage of devices, architectures, and prominent applications, providing students with insight into the mathematical and physical principles, a practical understanding of component technology and performance, a grasp of system design and analysis, and a familiarity with architectures for selected but representative applications. Ideal for senior-level undergraduate and first year graduate students in electrical engineering and applied physics as well as practicing engineers and scientists, this accessible text also includes problem exercises, selected hints and solutions, extensive references, and MATLAB-based modeling (available via the World Wide Web at http://www.jhuapl.edu/public/books/OSPbook/firstpage.html). It also offers simulation tools to support students exploration of applications and to direct their learning towards the current technical literature. Numerous architectural diagrams are provided to help students understand and visualize important concepts and their implementation.

Table of Contents

Preface
Acknowledgments
Introduction
Bibliography
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 Forms
1.6. Linear Coordinate Transformation and Fourier Theorem
1.7. Examples of Magnification and Rotation
1.8. Two-Dimensional Impulse Functions: Properties and Fourier Transforms
1.9. Elementary Images and Their Fourier Properties
2. STOCHASTIC PROCESSES AND NONLINEAR SYSTEMS
2.1. Basic Concepts of Stochastic 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 GEOMETRICAL OPTICS
4.1. Overview
4.2. Fundamental Scalar and Vector Properies 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. Effect of Lens on a Wavefront
6.3. Fourier Transform Property of a Single Lens
6.4. Imaging Property of Lenses
6.5. Linear System Properties of Imaging Systems
6.6. Point Spread Function
6.7. Optical Transfer Function
6.8. Signal Processing Analogies for Optics
7. LIGHT SOURCES AND DETECTORS
7.1. Overview
7.2. Laser Principles of Operation
7.3. Light Emitting Diodes and Laser Diodes
7.4. Laser Diode Arrays
7.5. Output Light Detectors
7.6. Single detectors
7.7. Linear and Matrix Arrays
7.8. Optical Signal Processing Requirements
8. SPATIAL LIGHT MODULATORS
8.1. Overview
8.2. 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 Architectures
9.4. Spectrum Analysis
9.5. Space-Integrating Spectrum Analyzer
9.6. Time integrating specturm 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 Circumventing 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. Matrix-Vector Multiplication
12.4. Optical Neural Networks
Each chapter ends with Problem Exercises and a Bibliography
Appendix A: Mathematical Tables
Appendix B: Annotated Bibliography
Appendix C: Software for Modeling and Visualization
Appendix D: Hints and Solutions to Selected Problems
Index