Title of article
On Missing Data Treatment for Degraded Video and Film Archives: A Survey and a New Bayesian Approach
Author/Authors
A. C. Kokaram، نويسنده ,
Issue Information
روزنامه با شماره پیاپی سال 2004
Pages
19
From page
397
To page
415
Abstract
Image sequence restoration has been steadily gaining
in importance with the increasing prevalence of visual digital
media. The demand for content increases the pressure on archives
to automate their restoration activities for preservation of the
cultural heritage that they hold. There are many defects that
affect archived visual material and one central issue is that of
Dirt and Sparkle, or “Blotches.” Research in archive restoration
has been conducted for more than a decade and this paper places
that material in context to highlight the advances made during
that time. The paper also presents a new and simpler Bayesian
framework that achieves joint processing of noise, missing data,
and occlusion.
Keywords
Gibbs sampling , image processing , Marginalization , MarkovChain Monte Carlo , Motion estimation , noise reduction , video restoration. , Bayesian inference , Autoregressive models , factored sampling , film and video post production , compositionsampling , missing data reconstruction , Video processing
Journal title
IEEE TRANSACTIONS ON IMAGE PROCESSING
Serial Year
2004
Journal title
IEEE TRANSACTIONS ON IMAGE PROCESSING
Record number
396933
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