LEC # | TOPICS | KEY DATES |
---|---|---|
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 |