Bayesian image interpolation using Markov random fields driven by visually relevant image features

In this paper we present a Markov Random Field (MRF) based image interpolation procedure suited to both noise-free and noisy measurements. Specifically, after introducing a MRF characterized by means of a novel complex line process representing the visually relevant image features, we derive the glo...

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Veröffentlicht in:	Signal processing. Image communication 2013-09, Vol.28 (8), p.967-983
Hauptverfasser:	Colonnese, S., Rinauro, S., Scarano, G.
Format:	Artikel
Sprache:	eng
Schlagworte:	Bayesian analysis Bayesian estimation Computational efficiency Gaussian Image interpolation Interpolation Magnetorheological fluids Markov processes Markov random fields Mathematical analysis
Online-Zugang:	Volltext
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