We present an efficient solution to mitigate phase unwrapping (PhU) errors that can affect a sequence of multi-temporal differential synthetic aperture radar (SAR) interferograms. To this aim, we propose a strategy that, starting from a properly chosen network of differential interferograms, complements PhU operations with an advanced multi-temporal region-growing (RG) procedure that exploits the space-time relationships among the computed interferograms. In particular, the proposed method implements an iterative procedure that, at each step, allows correcting a sequence of previously unwrapped interferograms at one selected pixel, namely candidate pixel, by exploiting the (unwrapped) phase values at its neighbouring 'seed' pixels (i.e. the ones already correctly unwrapped). Following their estimation, the unwrapped phases are then used to retrieve surface deformation products, such as mean deformation velocity maps and displacement time series, through (advanced) small baseline differential SAR interferometry (DInSAR) techniques. The effectiveness of the presented RG PhU algorithm is demonstrated by analysing a data set of SAR images acquired by the European Remote Sensing (ERS)-1/2 sensors over the megacity area of Istanbul, Turkey.
A region-growing technique to improve multi-temporal DInSAR interferogram phase unwrapping performance
A Pepe;M Manzo;F Casu;
2013
Abstract
We present an efficient solution to mitigate phase unwrapping (PhU) errors that can affect a sequence of multi-temporal differential synthetic aperture radar (SAR) interferograms. To this aim, we propose a strategy that, starting from a properly chosen network of differential interferograms, complements PhU operations with an advanced multi-temporal region-growing (RG) procedure that exploits the space-time relationships among the computed interferograms. In particular, the proposed method implements an iterative procedure that, at each step, allows correcting a sequence of previously unwrapped interferograms at one selected pixel, namely candidate pixel, by exploiting the (unwrapped) phase values at its neighbouring 'seed' pixels (i.e. the ones already correctly unwrapped). Following their estimation, the unwrapped phases are then used to retrieve surface deformation products, such as mean deformation velocity maps and displacement time series, through (advanced) small baseline differential SAR interferometry (DInSAR) techniques. The effectiveness of the presented RG PhU algorithm is demonstrated by analysing a data set of SAR images acquired by the European Remote Sensing (ERS)-1/2 sensors over the megacity area of Istanbul, Turkey.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.