Name
Abstract | ||
|---|---|---|
We present an efficient algorithm to mitigate noise effects in differential interferograms by exploiting the temporal relationships among a redundant set of small baseline interferograms. The core of the proposed technique is represented by the estimation of the (wrapped) filtered phase values associated to the available SAR acquisitions. This result is achieved by using conventional multi-look interferograms by applying a non-linear maximization procedure that exploits only phase information, and does not require any assumption on the statistics of the complex-valued SAR images involved in the interferogram generation. Subsequently, from the retrieved phase images, a filtered version of the original interferograms can be simply reconstructed and used to generate deformation time series by the conventional Small BAseline Subset (SBAS) approach. The experimental results, achieved by applying the proposed approach to a dataset consisting in 39 SAR data acquired from 2002 to 2010 over the Abruzzi (Central Italy) area confirm the effectiveness of the proposed method. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/IGARSS.2012.6351142 | IGARSS |
Keywords | Field | DocType |
small baseline subset approach,deformation time-series,ad 2002 to 2010,abruzzi,nonlinear maximization,small baseline subset (sbas),multilook interferogram,noise effect mitigation,central italy,remote sensing by radar,temporal relationship,geophysical image processing,small baseline interferogram,radar interferometry,time series,decorrelation noise,sbas-dinsar approach,sbas approach,coherence,image reconstruction,remote sensing,synthetic aperture radar,time series analysis,interferometry,noise | Computer vision,Noise effects,Computer science,Remote sensing,GNSS augmentation,Artificial intelligence,Maximization | Conference |
Volume | Issue | ISSN |
null | null | 2153-6996 E-ISBN : 978-1-4673-1158-8 |
ISBN | Citations | PageRank |
978-1-4673-1158-8 | 0 | 0.34 |
References | Authors | |
4 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yang Yang | 1 | 0 | 0.34 |
| Antonio Pepe | 2 | 183 | 30.06 |
| Mariarosaria Manzo | 3 | 41 | 10.53 |
| Riccardo Lanari | 4 | 199 | 50.16 |