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?
Illumination
image formation
Light dispersion
Optics
2D sampling
image processing
The different steps involved in image formation
Point Spread Function
Convolution
Digitization
Factors that affect image quality
Resolution: sensor
Noise
Artifacts: motion blur, compression, lens aberrations.
Computational Imaging Algorithms
How do you mathmatically model a imaging system
Forward Model
How do you denoise or deblurr an observed image
Solving the inverse for the forward model
Numerical Iterative Method
Total Variational Regularization
Deep Learning Diffusion Method
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