Automatic Digital Hologram Denoising by Spatiotemporal Analysis of Pixel-Wise Statistics (Articolo in rivista)

Type
Label
  • Automatic Digital Hologram Denoising by Spatiotemporal Analysis of Pixel-Wise Statistics (Articolo in rivista) (literal)
Anno
  • 2013-01-01T00:00:00+01:00 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
  • 10.1109/JDT.2013.2268936 (literal)
Alternative label
  • Leo, M.; Distante, C.; Paturzo, M.; Memmolo, P.; Locatelli, M.; Pugliese, E.; Meucci, R.; Ferraro, P. (2013)
    Automatic Digital Hologram Denoising by Spatiotemporal Analysis of Pixel-Wise Statistics
    in Journal of display technology
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Leo, M.; Distante, C.; Paturzo, M.; Memmolo, P.; Locatelli, M.; Pugliese, E.; Meucci, R.; Ferraro, P. (literal)
Pagina inizio
  • 904 (literal)
Pagina fine
  • 909 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#url
  • http://www.scopus.com/inward/record.url?eid=2-s2.0-84888368666&partnerID=q2rCbXpz (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
  • 9 (literal)
Rivista
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#pagineTotali
  • 6 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroFascicolo
  • 11 (literal)
Note
  • ISI Web of Science (WOS) (literal)
  • Scopu (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • CNR-Istituto Nazionale di Ottica, 73010 Arnesano (LE), Italy; CNR-Istituto Nazionale di Ottica, Comprensorio -A. Olivetti, I-80078 Pozzuoli (Naples), Italy; Advanced Biomaterials for Health Care CRIB, Istituto Italiano di Tecnologia, Napoli 80125, Italy; CNR-Istituto Nazionale di Ottica, I-50125 Firenze, Italy (literal)
Titolo
  • Automatic Digital Hologram Denoising by Spatiotemporal Analysis of Pixel-Wise Statistics (literal)
Abstract
  • In this paper, a new technique to reduce the noise in a reconstructed hologram image is proposed. Unlike all the techniques in the literature, the proposed approach not only takes into account spatial information but also temporal statistics associated with the pixels. This innovative solution enables, at first, the automatic detection of the areas of the image containing the objects (foreground). This way, all the pixels not belonging to any objects are directly cleaned up and the contrast between objects and background is consistently increased. The remaining pixels are then processed with a spatio-temporal filtering which cancels out the effects of speckle noise, while preserving the structural details of the objects. The proposed approach has been compared with other common speckle denoising techniques and it is found to give better both visual and quantitative results. (literal)
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