Imaging System (WIP)

Introduction

• What is an imaging system?

An imaging system extracts geometric information about the objects in this 3D space using different sensing modalities based on principles of physics. A modality in this context is a type of imaging method that uses different sensing principles such as  light waves, X ray radiation, strong magnetic field, acoustic sound waves, and raidio active emissions.  An example imaging system in a camera, which uses light wave as the information to generate a 2D project of this 3D world. This sytem contains a mechical shutter for control time exposure, a focal len to change depth of view, a imager sensor to digitize color and intensity information fron light array, compute engine for image processing such as high dynamic range.

• Different types of imaging systems

• The physical principles behind imaging systems

Image formation

• How do imaging systems work?

  1. Illumination

  2. image formation

     1. Light dispersion

     2. Optics

     3. 2D sampling

  3. image processing

• The different steps involved in image formation

  1. Point Spread Function

  2. Convolution

  3. Digitization

• Factors that affect image quality

  1. Resolution: sensor 

  2. Noise

  3. Artifacts: motion blur, compression, lens aberrations.

Computational Imaging Algorithms

• How do you mathmatically model a imaging system

  1. Forward Model

• How do you denoise or deblurr an observed image

  1. Solving the inverse for the forward model

     1. Numerical Iterative Method

        1. Total Variational Regularization

     2. Deep Learning Diffusion Method

        1. Deep image prior 

Applications of imaging systems

• Medical imaging

• Industrial imaging

• Security imaging

• Other applications

Conclusion

• Summary of the key points

• Future trends in imaging systems