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Details of Grant 

EPSRC Reference: GR/S70098/01
Title: Digital Restoration of Film Archives
Principal Investigator: Vlachos, Dr T
Other Investigators:
Researcher Co-Investigators:
Project Partners:
Department: Sch of Electronics & Physical Sciences
Organisation: University of Surrey
Scheme: Standard Research (Pre-FEC)
Starts: 01 July 2004 Ends: 30 September 2007 Value (£): 225,735
EPSRC Research Topic Classifications:
Image & Vision Computing Multimedia
EPSRC Industrial Sector Classifications:
Creative Industries
Related Grants:
Panel History:  
Summary on Grant Application Form
The emergence of new multimedia and broadcasting outlets is creating an insatiable demand for archive audiovisual material a substantial amount of which is in urgent need of restoration. Unfortunately public access to assets of unique cultural value is limited by technological factors which make restoration an unrealistic proposition due to excessive reliance on labour-intensive manual operations. This project aims at overcoming these limitations and deliver automated restoration tools that target two of the most common and perceptually significant film-related artefacts namely flicker and unsteadiness. These signature artefacts interfere substantially with the viewing experience, have the potential of concealing essential detail and are detrimental to the efficiency of digital compression used in the television and multimedia delivery chains. The project will use recent advances in film restoration as a launch pad for probing far beyond the boundaries of the current state-of-the-art. For the correction of flicker a novel approach based on better understanding and modelling of the contributing causes will be explored. A non-linear correction model derived directly from the Hurter-Driffield characteristic will be used and further developed to benefit from motion estimation and motion compensated filtering methodologies. The model will also evolve to accommodate spatial variations of flicker on the image plane. For the correction of unsteadiness the proposed approach aims at overcoming the limitations imposed by translational motion estimation models used in state-of-the-art systems by pioneering the use of more complex models, such as affine and bilinear, in a robust statistical framework designed to minimise the influence of camera and scene motion. The research will be undertaken at the School of Electronics and Physical Sciences of the University of Surrey, a 5-star research-rated department, and will benefit from the unique expertise, infrastructure and specialist support of the Centre for Vision, Speech and Signal Processing an internationally acclaimed research centre of excellence in the field of image processing and computer vision.
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Organisation Website: http://www.surrey.ac.uk