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Optical Engineering >> Content Detail



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G = Amazon logo Goodman, Joseph W. Statistical Optics. Hoboken, NJ: Wiley-Interscience, 2000. ISBN: 9780471399162.
B = Amazon logo Bertero, Mario, and Patrizia Boccacci. Introduction to Inverse Problems in Imaging. London, NY: Taylor & Francis, 1998. ISBN: 9780750304351.


LEC #TOPICSREADINGS
1Introduction: Statistical Optics, Inverse Problems
2Fourier Optics Overview
3Random Variables: Basic Definitions, MomentsG2.1-4
4Random Variables: Transformations, GaussiansG2.5-9
5Examples: Probability Theory and StatisticsNotes
6Random Processes: Definitions, Gaussian, PoissonG3.1-7
7Examples: Gaussian ProcessesNotes
8Random Processes: Analytic RepresentationG3.8-10
9Examples: Complex Gaussian ProcessesNotes
101st-Order Light StatisticsG4.1-4
11Examples: Thermal and Laser LightNotes
122nd-Order Light Statistics: CoherenceG5.1-3
13Example: Integrated IntensityG6.1
14The van Cittert-Zernicke TheoremG5.4-6
15Example: Diffraction from an ApertureG5.7
16The Intensity Interferometer

Speckle
G6.3

7.5
17Examples: Stellar Interferometer, Radio Astronomy,
Optical Coherence Tomography
Notes
18Effects of Partial Coherence on ImagingClass
19Information Theory: Entropy, Mutual InformationNotes
20Example: Gaussian ChannelsNotes
21Convolutions, Sampling, Fourier Transforms

Information-Theoretic View of Inverse Problems
B2.1-7

and Notes
22Imaging Channels

Regularization
B3.1-5,

5.1-3
23Inverse Problem Case Study: Tomography

Radon Transform, Slice Projection Theorem
B8.2-3

9.5, 11.1
24Filtered BackprojectionB11.2-3
25Super-Resolution and Image RestorationB10.1-5, 11.4-5
26Information-Theoretic Performance of Inversion MethodsClass

 








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