The AURORA project (AUtomated Restoration of ORiginal Film Archives) is an E.U. funded ACTS project which began in September of 1996. The partners include three broadcasters and holders of archives, The Insitut National L'Audiovisuel (INA), The British Broadcasting Corporation, Radiotelevisao Portuguesa, two industrial companies, Snell and Wilcox, Societe Generale de Teleinformatic, and the signal processing groups of three academic institutions the Digital Media Institute, (Tampere, Finland) Delft University (The Netherlands) and Cambridge University Engineering Dept. (U.K). The project, coordinated by INA, has the sole purpose of designing new tools for video restoration/enhancement. This goal is motivated by the lack of a complete set of advanced manipulation tools which would otherwise allow the more complete exploitation of the archive holdings of many of the larger broadcasters. Furthermore, with the oncoming rise in Digital Video broadcasting a higher demand on quality and quantity of archive material is perceived; hence the requirement for real time restoration devices is set to become more exacting. The project therefore considers the usual cornerstones of video restoration : noise reduction, missing data detection and reconstruction, reduction of image unsteadiness; as well as the associated software and hardware implementation issues. This paper concentrates on new developments at Cambridge University with respect to missing data reconstruction using probabilistic formulations.
[1]
Donald Geman,et al.
Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images
,
1984
.
[2]
K. Riedel.
Numerical Bayesian Methods Applied to Signal Processing
,
1996
.
[3]
Anil C. Kokaram,et al.
A System for Reconstruction of Missing Data in Image Sequences Using Sampled 3D AR Models and MRF Motion Priors
,
1996,
ECCV.
[4]
Stan Z. Li,et al.
Markov Random Field Modeling in Computer Vision
,
1995,
Computer Science Workbench.
[5]
Anil C. Kokaram,et al.
Detection of missing data in image sequences
,
1995,
IEEE Trans. Image Process..
[6]
K OrJ.
Numerical Bayesian methods applied to signal processing
,
1996
.
[7]
Anil C. Kokaram,et al.
Interpolation of missing data in image sequences
,
1995,
IEEE Trans. Image Process..
[8]
Robin D. Morris,et al.
Image Sequence Restoration Using Gibbs Distributions
,
1995
.