Signal Extrapolation for Image and Video Error Concealment Using Gaussian Processes with Adaptive non-Stationary Kernels

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TitleSignal Extrapolation for Image and Video Error Concealment Using Gaussian Processes with Adaptive non-Stationary Kernels
Publication TypeJournal Article
Year of Publication2012
JournalIEEE Signal Processing Letters
Volume19
Issue10
Start Page700
Date Published08/2012
ISSN1070-9908
Accession Number13033745
AbstractIn this letter, a new adaptive Gaussian process (GP) frame work for signal extrapolation is proposed. Signal extrapolation is an essential task in many applications such as concealment of corrupted data in image and video communications. While possessing many interesting properties, Gaussian process priors with inappropriate stationary kernels may create extremely blurred edges in concealed areas of the image. To address this problem, we propose a Gaussian process framework with adaptive non-stationary kernels. The proposed adaptive kernel functions are defined based on the hypothesized edges of the missing areas. Experimental results verify the effectiveness of the proposed method compared to the existing state of the art algorithms, based on objective and subjective evaluations.
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DOI<a href="http://dx.doi.org/10.1109/LSP.2012.2213593&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp

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