PRIAR (Pattern Recognition Image Augmented Res- olution) is a tool that uses the information gained through pattern-recognition to enhance resolution for low quality images, and to allow the end user to explore, recognize and super- resolve low-resolution images. In this paper, we present the basic functionality of the PRIAR algorithms, that have been implemented with Matlab classes and functions. These classes can be easily combined, which has the advantage that one can adapt the simulation programs to various applications. Here, we consider the application of PRIAR to image reproducing cells recorded with scanning probe microscopy.

PRIAR (Pattern Recognition Image Augmented Resolution) - a tool to combine pattern-recognition with super-resolution

Righi M;D'Acunto M;
2014

Abstract

PRIAR (Pattern Recognition Image Augmented Res- olution) is a tool that uses the information gained through pattern-recognition to enhance resolution for low quality images, and to allow the end user to explore, recognize and super- resolve low-resolution images. In this paper, we present the basic functionality of the PRIAR algorithms, that have been implemented with Matlab classes and functions. These classes can be easily combined, which has the advantage that one can adapt the simulation programs to various applications. Here, we consider the application of PRIAR to image reproducing cells recorded with scanning probe microscopy.
2014
Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" - ISTI
Inglese
OGRW2014 - 9th International Conference on Open German­ Russian Workshop on Pattern Recognition and Image Understanding
Sì, ma tipo non specificato
1-5 December 2014
Koblenz, Germany
Signal analisys
Super-resolution
Pattern-recognition
Moduli CNR: 2269-ICT.P10.012.001; Codice Puma: /cnr.isti/2014-A2-080
3
restricted
Righi, M; D'Acunto, M; Salvetti, O
273
info:eu-repo/semantics/conferenceObject
04 Contributo in convegno::04.01 Contributo in Atti di convegno
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/261394
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