Emmanuel Trouvé

Improving phase unwrapping techniques by the use of local frequency estimates

In multipass spaceborne synthetic aperture radar (SAR) interferometry, the two acquisitions often present low correlation levels and very noisy phase measurements that are incompatible with automatic phase unwrapping. Instead of dealing with many residues due to erroneous-wrapped phase differences, the authors propose to use the local frequency as measured by a spectral analysis algorithm presented in a previous paper, E. Trouve et al. (1996). For this purpose, the authors present two conventional unwrapping algorithms, one local and the other global, which they revisit to benefit from the robust focal frequency estimates. For a local approach based on path-following techniques, they use the frequency estimates in a slope-compensated filter that extend the complex averaging up to a sufficient number of looks to eliminate residues due to the noise. Then they connect residues due to noninterferometric features along mask components resulting from the detection of layovers and uncorrelated areas. For a global approach, such as the weighted least-squares methods, they demonstrate that the use of noisy discrete phase gradient leads to a biased solution. To avoid this drawback, they propose to use the local frequency estimate and associated measure of confidence as phase gradient and weight. Results are presented on both topographic and differential interferograms obtained from the ERS-1 European radar satellite over various landscapes and the displacement field of the Landers 1992 earthquake.

Fringe detection in noisy complex interferograms.

A new algorithm to estimate the two-dimensional local frequencies of phase interferometric data is described. With a complex sine-wave model, demonstration is given that a conventional multiple-signal classification (MUSIC) algorithm can be used in spite of multiplicative noise perturbations. A faster algorithm dedicated to the processing of interferograms is developed and a measure of confidence in the estimate is proposed. We studied numerical performances using synthetic fringes. As a result of the frequency estimation, knowledge of the fringe local width and orientation can be applied to restore noisy phase data. Results of a complex phase filter are presented for real interferograms obtained from synthetic aperture radar images.

Change analysis of dual polarimetric Sentinel-1 SAR image time series using stationary wavelet transform and change detection matrix

This paper provides initial change detection results on a time series of 11 dual polarimetric IW level-1 single look complex (SLC) Sentinel-1 SAR images acquired in descending pass over Chamonix Mont-Blanc, France. The changed and unchanged information in the time series is identified in the change detection matrix (CDM) constructed by similarity cross tests between wavelet extracted features issued from stationary wavelet transform (SWT). The analysis from multiscale decomposition allows the separation of multidate pixel changes in low frequencies from changes in high frequencies. The index of change dynamics derived from CDM enables to analyze the temporal evolution of the observed area.