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