| 1 |
Introduction: Statistical Optics, Inverse Problems |
Homework 1 Posted (Fourier Optics Overview) |
| 2 |
Fourier Optics Overview |
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| 3 |
Random Variables: Basic Definitions, Moments |
Homework 1 Due
Homework 2 Posted (Probability I) |
| 4 |
Random Variables: Transformations, Gaussians |
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| 5 |
Examples: Probability Theory and Statistics |
Homework 2 Due
Homework 3 Posted (Probability II) |
| 6 |
Random Processes: Definitions, Gaussian, Poisson |
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| 7 |
Examples: Gaussian Processes |
Homework 3 Due
Homework 4 Posted (Random Processes) |
| 8 |
Random Processes: Analytic Representation |
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| 9 |
Examples: Complex Gaussian Processes |
Homework 4 Due
Project 1 Begins |
| 10 |
1st-Order Light Statistics |
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| 11 |
Examples: Thermal and Laser Light |
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| 12 |
2nd-Order Light Statistics: Coherence |
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| 13 |
Example: Integrated Intensity |
Project 1 Report Due
Project 2 Begins |
| 14 |
The van Cittert-Zernicke Theorem |
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| 15 |
Example: Diffraction from an Aperture |
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| 16 |
The Intensity Interferometer
Speckle |
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| 17 |
Examples: Stellar Interferometer, Radio Astronomy, Optical Coherence Tomography |
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| 18 |
Effects of Partial Coherence on Imaging |
Project 2 "Lecture-Style" Presentations (2 Hours) |
| 19 |
Information Theory: Entropy, Mutual Information |
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| 20 |
Example: Gaussian Channels |
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| 21 |
Convolutions, Sampling, Fourier Transforms
Information-Ttheoretic View of Inverse Problems |
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| 22 |
Imaging Channels
Regularization |
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| 23 |
Inverse Problem Case Study: Tomography
Radon Transform, Slice Projection Theorem |
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| 24 |
Filtered Backprojection |
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| 25 |
Super-Resolution and Image Restoration |
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| 26 |
Information-Theoretic Performance of Inversion Methods |
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