Computational optical imaging

Summary

Modern imaging systems combine traditional optical devices (lenses, endoscopes, cameras, laser scanners, etc) with digital computers. In this course we learn how to use computational tools to simulate the optical system and combine them with neural networks that process the optical images

Content

Keywords

Optical imaging, optical instruments, optical design, performance analyis, aberrations, resolution and contrast, microscopy

Learning Prerequisites

Required courses

"MICRO-321 Ingenierie Optique" or any Bachelor level optics course

Recommended courses

"MICRO-321 Ingenierie Optique" or any Bachelor level optics course

Important concepts to start the course

Matrix calculations, Fourier transformation, Electromagnetic waves, refraction and reflection, polarization, signal filtering, basics of geometrical optics

Learning Outcomes

By the end of the course, the student must be able to:

• Sketch optical systems
• Estimate performance of optical systems
• Analyze imaging systems and the image quality
• Compute Digital twin

Transversal skills

• Set objectives and design an action plan to reach those objectives.
• Communicate effectively with professionals from other disciplines.
• Continue to work through difficulties or initial failure to find optimal solutions.

Teaching methods

Lecturing with exercises

Expected student activities

During semester evaluation. Final written exam in the last day of class.

Supervision

Resources

Virtual desktop infrastructure (VDI)

No

Bibliography

B.A. Saleh and M.C. Teich, Fundamental of photonics (2007)

J.W. Goodman, Introduction to Fourier optics (1996)

Notes/Handbook

Course material and slides covering geometrical and matrix optics, Fourier optics, microscopy are published on Moodle

Moodle Link

• https://go.epfl.ch/MICRO-421