Inverse Problems in Imaging

Inverse Problems in Imaging

Internship Description

Inverse problems are abundant in the field of imaging, and range from simple image processing tasks such as denoising and deblurring to full-scale reconstruction problems like computed tomography (reconstructing 3D volumes from 2D projections). The purpose of this internship is to learn about inverse problems, and critical techniques for solving them, including convex and non-convex optimization, sparse coding, and compressive sensing.


This project requires some familiarity with basic numerical methods as well as programming skills. Close collaboration with other team members is expected. Possibility for co-authoring a scientific article in a conference or journal.

Faculty Name

Wolfgang Heidrich

Field of Study