A P-band Pol-InSAR dataset acquired over a maritime pine forest is evaluated for forest height estimation. First, a time-frequency inversion methodology is presented. Good results have been obtained (2 m RMS error over 27 stands). However, since the method is adapted to airborne SAR data, we further investigate methods that could be used to invert spaceborne SAR data. Possible adaptations of th...

Here, we introduce the blind subspace deconvolution (BSSD) problem, which is the extension of both the blind source deconvolution (BSD) and the independent subspace analysis (ISA) tasks. We treat the undercomplete BSSD (uBSSD) case. Applying temporal concatenation we reduce this problem to ISA. The associated ‘high dimensional’ ISA problem can be handled by a recent technique called joint f-dec...

Compression of multispectral images (obtained from sensors that sample in both the spatial and the spectral domains) is important for reducing the transmission and storage requirements of such data. This article describes versatile software developed to simulate a family of compression algorithms. Two algorithms are selected as the most suitable for implementation. The first is a moderately hig...

Polarimetric Synthetic Aperture Radar (SAR) Interferometry (Pol-InSAR) is a radar remote sensing technique, based on the coherent combination of radar polarimetry (Pol-SAR) and SAR interferometry (InSAR) which is substantially more sensitive to structural parameters of forest volume scatterers (e.g. forest) than conventional interferometry or polarimetry alone. However, temporal decorrelation i...

The purpose of the present work is to establish decorrelation estimates for some random discrete Schrödinger operator in dimension one. We prove that the Minami estimates are consequences of the Wegner estimates and Localization. We also prove decorrelation estimates at distinct energies for the random hopping model and Schrödinger operators with alloy-type potentials. These results are used to...

We address the problem of removing correlation from sets of states while preserving as much local quantum information as possible. We prove that states obtained from universal cloning can only be decorrelated at the expense of complete erasure of local information (i.e., information about the copied state). We solve analytically the problem of decorrelation for two qubits and two qumodes (harmo...

In this paper, we consider the problem of blind separation of causal minimum phase convolutive mixtures of two sources. We study in detail the so-called decorrelation approach. It consists in finding a causal minimum phase filter which, driven by the observations, produces decorrelated outputs. It is well established that this approach allows to separate the sources if the mixing filter is a no...

In this paper we analyze and extend a class of adaptive networks for second order blind decorrelation of instantaneous signal mix tures Firstly we compare the performance of the decorrelation neural network employing global knowledge of the adaptive co e cients in with a similar structure whose coe cients are adapted via local output connections in Through statistical analyses the convergence b...

Recent developments in freehand 3D ultrasound (US) have shown how image registration and speckle decorrelation methods can be used for 3D reconstruction instead of relying on a tracking device. Estimating elevational separation between untracked US images using speckle decorrelation is error prone due to the uncertainty that plagues the correlation measurements. In this paper, using maximum ent...

Much interest is continuing to grow in advanced interferometric SAR methods for full 3D imaging, in particular of volumetric forest scatterers. Multibaseline SAR tomographic elevation beam forming, i.e. spatial spectral estimation, is a promising technique in this framework. In this paper, the important effect of temporal decorrelation during the repeat pass multibaseline acquisition is analyze...