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G =

Goodman, Joseph W. Statistical Optics. Hoboken, NJ: Wiley-Interscience, 2000. ISBN: 9780471399162.
B =

Bertero, Mario, and Patrizia Boccacci. Introduction to Inverse Problems in Imaging. London, NY: Taylor & Francis, 1998. ISBN: 9780750304351.

LEC #	TOPICS	READINGS
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

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