Numerical Methods in imaging

 
 

Computational Imaging is a growing field with applications to medical, geophysical and many other disciplines. Numerical methods play an important role in this field, combining robust statistics, numerical linear algebra, numerical optimization and PDE’s. The goal of this course is to introduce the students into this inter-disciplinary topic. We will cover:


  1. 1.An introduction to computational imaging and inverse problems

  2. 2.Tomography, image debluring and super resolution

  3. 3.Image registration and optical flow

  4. 4.Images obtained by parameter identification

  5. 5.Uncertainty in imaging

6. Various topics such as numerical optimization, discretization and PDE’s

 

The course is a hands-on course. We will use different numerical tool and program in matlab.

 

Course DescRiption

Evaluation

Grading is based on 4 homework assignments and a final project. Ideally, the project will be a part of your thesis.

Books

We will use the following books for different parts of the course

* Image debluring (Hansen, Nagy, O’Leary)

  1. *Numerical methods for image registration (Modersitzki)

  2. *Computational methods in inverse problems (Vogel)

  3. *Statistical and Computational Inverse Problems (Kaipio, Somersalo)

Mfiles