| 1 |
Introduction: Statistical Optics, Inverse Problems |
|
| 2 |
Fourier Optics Overview |
|
| 3 |
Random Variables: Basic Definitions, Moments |
G2.1-4 |
| 4 |
Random Variables: Transformations, Gaussians |
G2.5-9 |
| 5 |
Examples: Probability Theory and Statistics |
Notes |
| 6 |
Random Processes: Definitions, Gaussian, Poisson |
G3.1-7 |
| 7 |
Examples: Gaussian Processes |
Notes |
| 8 |
Random Processes: Analytic Representation |
G3.8-10 |
| 9 |
Examples: Complex Gaussian Processes |
Notes |
| 10 |
1st-Order Light Statistics |
G4.1-4 |
| 11 |
Examples: Thermal and Laser Light |
Notes |
| 12 |
2nd-Order Light Statistics: Coherence |
G5.1-3 |
| 13 |
Example: Integrated Intensity |
G6.1 |
| 14 |
The van Cittert-Zernicke Theorem |
G5.4-6 |
| 15 |
Example: Diffraction from an Aperture |
G5.7 |
| 16 |
The Intensity Interferometer
Speckle |
G6.3
7.5 |
| 17 |
Examples: Stellar Interferometer, Radio Astronomy,
Optical Coherence Tomography |
Notes |
| 18 |
Effects of Partial Coherence on Imaging |
Class |
| 19 |
Information Theory: Entropy, Mutual Information |
Notes |
| 20 |
Example: Gaussian Channels |
Notes |
| 21 |
Convolutions, Sampling, Fourier Transforms
Information-Theoretic View of Inverse Problems |
B2.1-7
and Notes |
| 22 |
Imaging Channels
Regularization |
B3.1-5,
5.1-3 |
| 23 |
Inverse Problem Case Study: Tomography
Radon Transform, Slice Projection Theorem |
B8.2-3
9.5, 11.1 |
| 24 |
Filtered Backprojection |
B11.2-3 |
| 25 |
Super-Resolution and Image Restoration |
B10.1-5, 11.4-5 |
| 26 |
Information-Theoretic Performance of Inversion Methods |
Class |