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Imaging

Image and video data are one of the largest and fastest growing sources of information and present some of the biggest challenges for data science due to their data volume and complexity. Image analysis is important in a wide range of research areas: from the detection of galaxies in astronomical datasets, to the tracking of features in developmental biology, through to the analysis and restoration of priceless artworks. 

The explosion in data from such sources makes their unaided processing and interpretation by humans impossible, and requires the development of automated storage, management, processing and analysis algorithms.  Moreover, certain acquisition devices (such as magnetic resonance tomography or remote sensing of the atmosphere) do not immediately provide us with the kind of information relevant to our needs. Mathematical inversion algorithms are needed to extract this information from the physical and statistical laws that relate the measurements with the image.

Cambridge has a wealth of expertise in image analysis, from theory and algorithm design, to the development of methods for feature detection, tracking and noise removal.  Browse the researcher profiles below, or contact us for more information. 

Champions: 

People specializing in this area