http://www.cnr.it/ontology/cnr/individuo/prodotto/ID186710
Robust estimation of image fractal dimension based on pyramidal decomposition (Contributo in atti di convegno)
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- Robust estimation of image fractal dimension based on pyramidal decomposition (Contributo in atti di convegno) (literal)
- Anno
- 1999-01-01T00:00:00+01:00 (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
- 10.1109/ICECS.1999.812345 (literal)
- Alternative label
B. Aiazzi; L. Alparone; S. Baronti; A. Bulletti; A. Garzelli (1999)
Robust estimation of image fractal dimension based on pyramidal decomposition
in IEEE ICECS '99: The 6th IEEE International Conference on Electronics, Circuits and Systems, Pafos, Cipro, 5-8 Settembre 1999
(literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
- B. Aiazzi; L. Alparone; S. Baronti; A. Bulletti; A. Garzelli (literal)
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- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#url
- http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=812345 (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#titoloVolume
- Proceedings of IEEE ICECS '99: The 6th IEEE International Conference on Electronics, Circuits and Systems (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#pagineTotali
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- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
- \"Nello Carrara\" IROE-CNR, Via Panciatichi, 64, 50127 Firenze, Italy
Dept. Electron. Engin., Univ. Firenze, Via S. Marta, 3, 50139 Firenze, Italy
\"Nello Carrara\" IROE-CNR, Via Panciatichi, 64, 50127 Firenze, Italy
Dept. lnform. Engin., Univ. of Siena, Via Roma, 56, 53100 Siena, Italy
Dept. lnform. Engin., Univ. of Siena, Via Roma, 56, 53100 Siena, Italy (literal)
- Titolo
- Robust estimation of image fractal dimension based on pyramidal decomposition (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#isbn
- Abstract
- A suited approach to calculate the fractal dimension of images comes from power spectra fractional Brownian motions: the ratio between powers at different scales is related to the persistence parameter H and, thus, to the fractal dimension D = 3 - H. The signal-dependent nature of speckle noise, however, prevents from a correct estimation of fractal dimension from Synthetic Aperture Radar (SAR) images. Here, we propose and assess a novel method to obtain D based on the multiscale decomposition provided by the normalized Laplacian pyramid (NLP), which is a bandpass representation obtained by dividing the layers of an LP by its expanded baseband and designed to yield noise that is signal-independent. Experiments on both synthetic and true SAR images corroborate the underlying assumptions. (literal)
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