About the Project
The focus of the project will be the development of a restoration algorithm capable of generating a high resolution image from the multiple low resolution images captured by the device. The project will offer a wide scope for investigating various computational imaging techniques, such as super-resolution, recovery of depth information, and image optimisation to achieve a particular goal, such as target tracking. One of the key challenges will be designing an algorithm capable of operating in real-time.
The first phase of the project will concentrate on developing a mathematical model of the Flat Imager and using simulated data to investigate suitable restoration algorithms. Subsequent stages will focus on the development of a prototype device and suitable hardware for both the imaging system itself, and the control/restoration software to run on. The final phase will be a demonstration of the hardware and software working together in real-time.
Due to the novelty of the approach, it may not be possible to create an imaging device exactly as described in the patent in the timescales of an EngD, i.e. a variable lenslet device operating in the IR waveband. Should this prove to be the case, the fall-back position will be to create a device that, for example, operates in a different waveband (e.g. visible) or uses fixed rather than variable lenslets. It is therefore important that the mathematical model and restoration techniques developed in the first phase of research can be adapted to these different designs.
The work will provide a balance between experimental laboratory work, programming, and theoretical analysis. The project is expected to further research into TOMBO-like imaging systems and image restoration algorithms for such devices.
* Thin Observation Module by Bound Optics
Candidates will have a 1st or 2:1 in Maths, Physics or a related field such as Electronic Engineering. Candidates will have an aptitude and interest in computational imaging techniques, such as super-resolution and sparse image reconstruction. The candidate will need to be comfortable in a self-led research project, but able to collaborate with a team of scientists and engineers when required.
A good understanding of signal processing techniques and theory will prove to be highly beneficial, as will experience with MATLAB, Python or other scientific programming language.
Flexible Research Working:
MBDA is committed to making work a comfortable and enjoyable experience. We are constantly improving our sites and facilities, creating a lively and open working environment that has earned us 11th place in the Sunday Times “Best Big Companies to Work For” ranking.
MBDA operate a flexi-time scheme, where employees can vary their start and end of work times around a set of core hours, in order to let you fit your work around your home life schedule. Further details are available on request.
EngD Stipend of approximately £20,000 plus fees paid.
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