In less than 100 years image systems have progressed from Prof. Harold (“Doc”) Edgerton’s stroboscope, which stopped a bullet in flight, to cameras that can achieve 5 trillion frames-per-second (fps) [Nature Photonics 8, 695-700, 2014] or visualise photons in flight [Nature Photonics 10, 23-26, 2016]. Advanced imaging techniques, however, generate massive and complex multi-dimensional (x, y, z, time, wavelength) datasets that are restricting achievable impact.
In this project, we will work with the award-winning (2015 Converge Challenge) Scottish spin-off, Photon Force, who provides cutting-edge CMOS single-photon sensor & picosecond timing arrays, to develop two innovative data processing approaches for real-time 3D ranging. We will introduce an innovative fog computing concept by brining data analysis close to the sensor front-ends (instead of reading out and post-processing image data as traditional approaches) to allow fast imaging. We will also adopt compressed sensing techniques to enhance the image acquisition. With the latest image sensor technologies and two innovative data analysis strategies, the project promises real-time 3D ranging/imaging that can be widely used for manufacturing (virtual prototyping), autonomous cars, robotics, human-machine interfaces & gaming, biomedical imaging or security surveillance. This project aligns with the areas Advanced Automation Systems and Real-time Data perfectly.
Funding DetailsThe studentship is supported by the Datalab, Photon Forces, Faculty of Science and Faculty of Engineering to cover UK/EU fees and stipends.
Primary Supervior Dr David Li https://www.strath.ac.uk/staff/lidaviddr/
Secondary Supervisor Dr Erfu Yang https://www.strath.ac.uk/staff/yangerfudr/
Nature Photonics 8, 695-700, 2014
Nature Photonics 10, 23-26, 2016
Opt. Express 24(7), 6899-6915, 2016
J. Biomed. Opt. 16(9), 096012, 2011
IEEE Electron. Dev. Lett. 33, 1589-1591, 2012
IEEE Trans. Electron. Dev. 58, 2028-2035, 2011