NORCAMA: Change analysis in SAR time series by likelihood ratio change matrix clustering
| hal.structure.identifier | Laboratoire Traitement et Communication de l'Information [LTCI] | |
| dc.contributor.author | SU, Xin | |
| hal.structure.identifier | Institut de Mathématiques de Bordeaux [IMB] | |
| dc.contributor.author | DELEDALLE, Charles-Alban | |
| hal.structure.identifier | Laboratoire Traitement et Communication de l'Information [LTCI] | |
| dc.contributor.author | TUPIN, Florence | |
| hal.structure.identifier | Wuhan University [China] | |
| dc.contributor.author | SUN, Hong | |
| dc.date.accessioned | 2024-04-04T03:17:50Z | |
| dc.date.available | 2024-04-04T03:17:50Z | |
| dc.date.issued | 2015-03 | |
| dc.identifier.issn | 0924-2716 | |
| dc.identifier.uri | https://oskar-bordeaux.fr/handle/20.500.12278/194345 | |
| dc.description.abstractEn | <p>This paper presents a likelihood ratio test based method of change detectionand classification for synthetic aperture radar (SAR) time series, namelyNORmalized Cut on chAnge criterion MAtrix (NORCAMA). This methodinvolves three steps: 1) multi-temporal pre-denoising step over the wholeimage series to reduce the effect of the speckle noise; 2) likelihood ratiotest based change criteria between two images using both the original noisyimages and the denoised images; 3) change classification by a normalized cutbased clustering-and-recognizing method on change criterion matrix (CCM).The experiments on both synthetic and real SAR image series show theeffective performance of the proposed framework.</p> | |
| dc.language.iso | en | |
| dc.publisher | Elsevier | |
| dc.subject.en | Change detection | |
| dc.subject.en | Change classification | |
| dc.subject.en | SAR time series | |
| dc.subject.en | Change criterion matrix | |
| dc.subject.en | Normalized cut | |
| dc.subject.en | Likelihood ratio test | |
| dc.title.en | NORCAMA: Change analysis in SAR time series by likelihood ratio change matrix clustering | |
| dc.type | Article de revue | |
| dc.subject.hal | Informatique [cs]/Traitement des images | |
| bordeaux.journal | ISPRS Journal of Photogrammetry and Remote Sensing | |
| bordeaux.page | 247-261 | |
| bordeaux.volume | 101 | |
| bordeaux.hal.laboratories | Institut de Mathématiques de Bordeaux (IMB) - UMR 5251 | * |
| bordeaux.institution | Université de Bordeaux | |
| bordeaux.institution | Bordeaux INP | |
| bordeaux.institution | CNRS | |
| bordeaux.peerReviewed | oui | |
| hal.identifier | hal-01185740 | |
| hal.version | 1 | |
| hal.popular | non | |
| hal.audience | Internationale | |
| hal.origin.link | https://hal.archives-ouvertes.fr//hal-01185740v1 | |
| bordeaux.COinS | ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=ISPRS%20Journal%20of%20Photogrammetry%20and%20Remote%20Sensing&rft.date=2015-03&rft.volume=101&rft.spage=247-261&rft.epage=247-261&rft.eissn=0924-2716&rft.issn=0924-2716&rft.au=SU,%20Xin&DELEDALLE,%20Charles-Alban&TUPIN,%20Florence&SUN,%20Hong&rft.genre=article |
Fichier(s) constituant ce document
| Fichiers | Taille | Format | Vue |
|---|---|---|---|
|
Il n'y a pas de fichiers associés à ce document. |
|||