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
Link To Document :
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