http://www.cnr.it/ontology/cnr/individuo/prodotto/ID189888
A robust change detection feature for Cosmo-SkyMed detected SAR images (Contributo in atti di convegno)
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- A robust change detection feature for Cosmo-SkyMed detected SAR images (Contributo in atti di convegno) (literal)
- Anno
- 2011-01-01T00:00:00+01:00 (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
- 10.1109/Multi-Temp.2011.6005064 (literal)
- Alternative label
B. Aiazzi, L. Alparone, S. Baronti, A. Garzelli, C. Zoppetti (2011)
A robust change detection feature for Cosmo-SkyMed detected SAR images
in IEEE MultiTemp 2011, 6th International Workshop on the Analysis of Multi-temporal Remote Sensing Images, Trento, Italia, 12-14 Luglio 2011
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- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
- B. Aiazzi, L. Alparone, S. Baronti, A. Garzelli, C. Zoppetti (literal)
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- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#url
- http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=6005064&contentType=Conference+Publications&sortType%3Dasc_p_Sequence%26filter%3DAND%28p_IS_Number%3A6005026%29%26pageNumber%3D2 (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#titoloVolume
- Proc. IEEE MultiTemp 2011, 6th International Workshop on the Analysis of Multi-temporal Remote Sensing Images (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#pagineTotali
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- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
- IFAC-CNR, Via Madonna del Piano, 10, I-50019 Sesto Fiorentino (FI), Italy
University of Florence, Dept. of Electronics and Telecom. Via Santa Marta, 3, I-50139 Firenze, Italy
IFAC-CNR, Via Madonna del Piano, 10, I-50019 Sesto Fiorentino (FI), Italy
University of Siena, Dept. of Information Engineering, Via Roma, 56, I-53100 Siena, Italy
University of Siena, Dept. of Information Engineering, Via Roma, 56, I-53100 Siena, Italy (literal)
- Titolo
- A robust change detection feature for Cosmo-SkyMed detected SAR images (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#isbn
- 978-1-4577-1202-9 (literal)
- Abstract
- Automated change analysis of multi-temporal SAR images is a challenging task due to the inherent noisiness of SAR imagery and the variability of the backscattering coefficient to the acquisition angle. Several methods have been proposed in the literature to improve the change detection performances with respect to the classical method based on the Log-Ratio operator. In this paper a pixel change feature is proposed and tested on true Cosmo-SkyMed detected images for damage assessment applications. The method does not require any despeckling pre-processing and is robust both to the acquisition noise and to possible variation of the acquisition angle in the two observations. (literal)
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