Calendar · Lecture Notes
MIT OpenCourseWare
Optical Engineering
- Instructor
- Prof. George Barbastathis
- Term
- Spring 2002
- Level
- Graduate
- What's inside
- 1 lecture note · 1 reading · 9 other files · 6 web pages
- Materials open
- MIT OCW
About this course
Source: MIT OpenCourseWare 2.717J Optical Engineering, Spring 2002, Prof. George Barbastathis — original course page on ocw.mit.edu ↗. License: CC BY-NC-SA 4.0. Study order: MIT's own listing order, section by section. Taken from MIT's published course files, downloaded from ocw.mit.edu on September 23, 2026. How RedLectern is built.
Materials are grouped the way MIT organized them. A verified, course-wide order has not been established here.
Before you start
Prerequisites are not listed here. Check MIT's own syllabus for this course.
How this course was organized
What's here, and what isn't
- A lecture sequence of 26 items is confirmed. It stays as organized materials rather than a full course order.
Not included here
1 item from the source could not be safely included:
- MIT's page format for this item wasn't recognized clearly enough to place it safely.
Materials by section
Grouped by section, as MIT organized them. Not sequenced or ordered.
Lecture Notes
- Introduction: Statistical Optics, Inverse Problems Download
- Fourier Optics Overview Download
- The Intensity Interferometer Speckle Download
- Information Theory: Entropy, Mutual Information Download
- Convolutions, Sampling, Fourier Transforms Information-Theoretic View of Inverse Problems Download
Assignments
- Homework 1: Fourier Optics Overview Download
- Homework 2: Introductory Probability Download
- Homework 3: More Probability Download
- Homework 4: Random Processes Download
- OCT schematic diagram Open ↗
- mr_ovation_b.jpg Open ↗
- Image of patient's brain acquired via 'Filtered Backprojection' technique Open ↗
- Aerial view of VLA. Caption: Very Large Array (VLA) Radio Telescope Open ↗
- mri_brain.jpg Open ↗
- An example photograph for Magnetic Resonance Imaging (MRI) Machine made by GE Medical Systems Open ↗
Course outline
Calendar · Lecture Notes
Lecture 2: Fourier Optics Overview
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Lecture 3: Random Variables: Basic Definitions, Moments
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Lecture 4: Random Variables: Transformations, Gaussians
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Lecture 5: Examples: Probability Theory and Statistics
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Lecture 6: Random Processes: Definitions, Gaussian, Poisson
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Lecture 7: Examples: Gaussian Processes
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Lecture 8: Random Processes: Analytic Representation
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Lecture 9: Examples: Complex Gaussian Processes
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Lecture 10: 1st-Order Light Statistics
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Lecture 11: Examples: Thermal and Laser Light
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Lecture 12: 2nd-Order Light Statistics: Coherence
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Lecture 13: Example: Integrated Intensity
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Lecture 14: The van Cittert-Zernicke Theorem
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Lecture 15: Example: Diffraction from an Aperture
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Lecture 16: The Intensity Interferometer Speckle
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Lecture 17: Examples: Stellar Interferometer, Radio Astronomy, Optical Coherence Tomography
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Lecture 18: Effects of Partial Coherence on Imaging
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Lecture 19: Information Theory: Entropy, Mutual Information
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Lecture 20: Example: Gaussian Channels
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Lecture 21: Convolutions, Sampling, Fourier Transforms Information-Ttheoretic View of Inverse Problems
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Lecture 22: Imaging Channels Regularization
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Lecture 23: Inverse Problem Case Study: Tomography Radon Transform, Slice Projection Theorem
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Lecture 24: Filtered Backprojection
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Lecture 25: Super-Resolution and Image Restoration
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Lecture 26: Information-Theoretic Performance of Inversion Methods
MIT OpenCourseWare, Prof. George Barbastathis, 2.717J Optical Engineering, Spring 2002.
License: CC BY-NC-SA 4.0 · Edition: Spring 2002 · Open the original course on OCW ↗
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