A Low-Memory, Straightforward and Fast Bilateral Filter Through Subsampling in Spatial Domain (Articolo in rivista)

Type
Label
  • A Low-Memory, Straightforward and Fast Bilateral Filter Through Subsampling in Spatial Domain (Articolo in rivista) (literal)
Anno
  • 2012-01-01T00:00:00+01:00 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
  • 10.1111/j.1467-8659.2011.02078.x (literal)
Alternative label
  • Banterle F., Corsini M., Cignoni P., Scopigno R. (2012)
    A Low-Memory, Straightforward and Fast Bilateral Filter Through Subsampling in Spatial Domain
    in Computer graphics forum (Online)
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Banterle F., Corsini M., Cignoni P., Scopigno R. (literal)
Pagina inizio
  • 19 (literal)
Pagina fine
  • 32 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#altreInformazioni
  • Grant agreement 231809 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
  • 31 (literal)
Rivista
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroFascicolo
  • 1 (literal)
Note
  • ISI Web of Science (WOS) (literal)
  • Scopu (literal)
  • PuMa (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • CNR-ISTI, Pisa, Italy; CNR-ISTI, Pisa, Italy; CNR-ISTI, Pisa, Italy; CNR-ISTI, Pisa, Italy; (literal)
Titolo
  • A Low-Memory, Straightforward and Fast Bilateral Filter Through Subsampling in Spatial Domain (literal)
Abstract
  • In this work we present a new algorithm for accelerating the colour bilateral filter based on a subsampling strategy working in the spatial domain. The base idea is to use a suitable subset of samples of the entire kernel in order to obtain a good estimation of the exact filter values. The main advantages of the proposed approach are that it has an excellent trade-off between visual quality and speed-up, a very low memory overhead is required and it is straightforward to implement on the GPU allowing real-time filtering. We show different applications of the proposed filter, in particular efficient cross-bilateral filtering, real-time edge-aware image editing and fast video denoising. We compare our method against the state of the art in terms of image quality, time performance and memory usage. (literal)
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