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PhD position in Image Processing - Perceptual Preferences Applied To Massive Super-Resolution and Image Editing

Applications are invited for an Engineering Doctorate (EngD) in the Department of Computer Science at the University College London (UCL) in conjunction with Anthropics Technology Ltd. This is a 4-year studentship, leading to the award of an Engineering Doctorate, which offers the opportunity to conduct research within an industrial context. This EPSRC (UK Research Council) funded studentship is available to UK citizens and EU nationals if a relevant connection with the UK has been established (usually by being resident for a period of three years immediately before the EngD). Applicants must fulfil EPSRC eligibility criteriaand the normal academic requirements for admission to study in the Department. This studentship will pay a tax-free stipend of approximately ?18,000 per year, plus tuition fees. EU students without a relevant connection to the UK can receive an award to cover tuition fees only.

The EngD post in this project will be based at both UCL (central London) and Anthropics Technology Ltd. (15 min away by Tube). The post is offered under the Virtual Environments, Imaging and Visualization programme, which is run by the EngD VEIV Centre, UCL Computer Science.

Project

This project aims at looking between the pixels: many image-editing operations require values sampled between pixel centres, let it be simple resizing operations, content-sensitive image enhancement or alpha matting. Usually, such values are determined using interpolation. The field of super-resolution, however, aims at inferring content between the pixel samples. Super-resolution of single images is an ill-posed problem. This project should research meaningful ways to infer, or to "hallucinate", inter-pixel content, by drawing from principles of human perception. A key component of the work shall investigate preferences of many human observers to crowd source a model of the additional details people would expect to appear when massively up-scaling an image. Such human-sourced image understanding may facilitate other novel image editing operations. The work is conducted in collaboration with Anthropics Technology Ltd., London, who are experts in putting powerful, high-level image operations at the fingertips of inexperienced users.

Applicants are required to have

• A bachelor degree (1st or 2.1 honours) or an MSc in Computer Science or related field;
• Good knowledge of computer graphics, image processing and mathematics;
• Strong programming skills, particularly C++, C, and Matlab;
• Good communication and presentation skills.

Informal enquiries on the project can be made to Dr Tim Weyrich (http://www.cs.ucl.ac.uk/staff/T.Weyrich/). For further information on the EngD Programme, see http://web4.cs.ucl.ac.uk/teaching/engd/ or contact Dr Jamie O'Brien ( Adres poczty elektronicznej jest chroniony przed robotami spamującymi. W przeglądarce musi być włączona obsługa JavaScript, żeby go zobaczyć. ).

To be considered, you must fill in the general UCL application form.  Please see http://www.ucl.ac.uk/prospective-students/graduate-study/application-admission/, where you can download the forms and guidelines. Make sure you specify Supervisor (Tim Weyrich), and EngD (?Perceptual Preferences?) on the ?Research Subject Area? part of the form. Please send the completed form to Dr Jamie O?Brien, Department of Computer Science, University College London, Gower Street, London WC1E 6BT.

If you need further assistance regarding our application process, please contact the EngD Centre Manager Dr Jamie O?Brien ( Adres poczty elektronicznej jest chroniony przed robotami spamującymi. W przeglądarce musi być włączona obsługa JavaScript, żeby go zobaczyć. )

PhD Student Position - image processing, opthamology

Applications are invited for a PhD studentship starting in the academic year 2011-12 to work with Dr Vincent Nourrit and Dr James Graham (University of Manchester) and 4D Optics Ltd.

The diagnosis and management of many ophthalmic conditions rely on assessment of retinal images. The application of adaptive optics (AO), a technique widely used in astronomy, to retinal imaging offers the potential to obtain images of the retina at previously unachievable resolution. As a consequence of the ultra high resolution of AO imaging systems, the area being imaged is relatively small and does not offer any landmark for the clinicians to localize the area of the fundus being imaged. This constitutes an impediment to the practical application of the technology in clinical practice. AO bio-microscopy of the retina allows imaging of the retina at the cellular scale. However at this scale it is extremely difficult to determine the location of the imaging field from the AO imaging. The objective of the project is to develop an accurate image processing algorithm to perform real time landmark tracking and to implement it within a dual scale system comprising an AO fundus camera and a standard wide field fundus camera.

This position is an opportunity to join a multidisciplinary environment and gain experience in several aspects of image processing, optics and ophthalmic instrumentation. In addition, the successful candidate will have the opportunity to work both in a business and academic environment.

The ideal candidate would combine good programming skills with proven experience of algorithm and software development, and a degree in mathematics or other numerate discipline. Knowledge of Matlab and/or numerical python and C is expected and knowledge of Mac OS, OpenCL would be an asset, as would experience in image processing or computer vision. The candidate should be able to demonstrate independence and curiosity and be able to lead the project forward.

Funding Notes:

This studentship is available to UK and other EU nationals (due to funding criteria) and provides fees and stipend subject to eligibility. Applicants should hold (or be about to obtain) a first or upper second class honours degree in a related area.

For further details please email Adres poczty elektronicznej jest chroniony przed robotami spamującymi. W przeglądarce musi być włączona obsługa JavaScript, żeby go zobaczyć.

To apply for this studentship please see: http://www.ls.manchester.ac.uk/phdprogrammes/apply.