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Computer Optics, 2019, Volume 43, Issue 1, Pages 115–122
DOI: https://doi.org/10.18287/2412-6179-2019-43-1-115-122 (Mi co611) 		 
IMAGE PROCESSING, PATTERN RECOGNITION

Video images compression and restoration methods based on optimal sampling

V. N. Drynkin, S. A. Nabokov, T. I. Tsareva

State Research Institute of Aviation Systems (GosNIIAS), Moscow, Russia
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DOI: https://doi.org/10.18287/2412-6179-2019-43-1-115-122
Abstract: The study proposes video images compression and restoration methods based on multidimensional sampling theory that provide four-fold video compression and subsequent real-time restoration with loss levels below visually perceptible threshold. The proposed methods can be used separately or along with any other video compression techniques, thus providing additional quadruple compression.
Keywords: video image compression, image reconstruction-restoration, three-dimensional image processing, quincuncial sampling, spatial filtering, spatial resolution.
Received: 20.06.2018
Accepted: 25.10.2018
Document Type: Article
Language: English
Citation: V. N. Drynkin, S. A. Nabokov, T. I. Tsareva, “Video images compression and restoration methods based on optimal sampling”, Computer Optics, 43:1 (2019), 115–122
Citation in format AMSBIB
\Bibitem{DryNabTsa19}
\by V.~N.~Drynkin, S.~A.~Nabokov, T.~I.~Tsareva
\paper Video images compression and restoration methods based on optimal sampling
\jour Computer Optics
\yr 2019
\vol 43
\issue 1
\pages 115--122
\mathnet{http://mi.mathnet.ru/co611}
\crossref{https://doi.org/10.18287/2412-6179-2019-43-1-115-122}
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