Cambridge Image Analysis
About the Group
The Cambridge Image Analysis Group (CIA) in DAMTP is specialising in the mathematics of digital image and video processing using partial differential equations and variational methods. Our research ranges from the modelling and analysis of such methods to their computational realisation and application. In particular, we are interested in
- Image retrieval and enhancement from corrupted and under sampled measurements
- Compressed sensing
- Sparsity promoting regularisation such as total variation and higher-order regularisation
- Image restoration
- Image segmentation and object tracking
- Large scale computing
- Applications in processing of photographs, biomedical imaging (MRI, PET/SPECT, microscopy imaging), arts restoration, forensics, just to name a few.
For more details see our Research page.
This group is mainly funded by EPSRC, the Leverhulme Trust, the Newton Trust,
the Wellcome Trust, and the Royal Society.
- July 2016. Carola-Bibiane Schönlieb is awarded a London Mathematical Society (LMS) Whitehead Prize "for her spectacular contributions to the mathematics of image analysis and inverse imaging problems".
- July 2016. Martin Benning is awarded a Leverhulme Trust Early Career Fellowship. The fellowship is set to start on 01. September 2016.
- May 2016. Isaac Newton Institute Programme on Variational methods and effective algorithms for imaging and vision, August - December 2017, Isaac Newton Institute, Cambridge, UK.
- May 2016. Launch of the Cantab Capital Institute for the Mathematics of Information. It accommodates research activity on fundamental mathematical problems and methodology for understanding, analyzing, processing and simulating data.
- April 2016. A paper of our group has been selected as a Highlight of 2015 of Inverse Problems: Matthias J. Ehrhardt et al. Joint reconstruction of PET-MRI by exploiting structural similarity.
- March 2016. Launch of the EPSRC Centre for Mathematical Imaging in Healthcare (CMiH) at the University of Cambridge. CMiH is part of a £10 million investment by the EPSRC to explore how mathematics and statistics can help clinicians to tackle serious health challenges such as cancer, heart disease and antibiotic resistant bacteria.