Displacement Estimation by Maximum-Likelihood Texture Tracking

Abstract

Abstract-This paper presents a novel method to estimate displacement by maximum-likelihood (ML) texture tracking. The observed polarimetric synthetic aperture radar (PolSAR) data-set is composed by two terms: the scalar texture parameter and the speckle component. Based on the Spherically Invariant Random Vectors (SIRV) theory, the ML estimator of the texture is computed. A generalization of the ML texture tracking based on the Fisher probability density function (pdf) modeling is introduced. For random variables with Fisher distributions, the ratio distribution is established. The proposed method is tested with both simulated PolSAR data and spaceborne PolSAR images provided by the TerraSAR-X (TSX) and the RADARSAT-2 (RS-2) sensors.Index Terms-Maximum-likelihood (ML), offset tracking, polarimetric synthetic aperture radar (SAR), spherically invariant random vectors, texture.

First Results of Monitoring Nature Conservation Sites in Alpine Region by Using Very High Resolution (VHR) X-Band SAR Data

“…For the detection of grazing/cutting event more precisely the ground truth data will be collected during the SAR acquisition days. In recent studies authors [43], [44] showed the application of Fisher probability distribution for SAR texture modeling and texture tracking for displacement estimation. In future works, the Fisher probability distributions will be also addressed to calculate the theoretical mean value of backscattering coefficients for different land cover and habitat types.…”

A Pattern-Based Method For Handling Confidence Measures While Mining Satellite Displacement Field Time Series: Application to Greenland Ice Sheet and Alpine Glaciers

“…If no redundant observations are available, then the stationarity of the flow direction can be used to derive confidence measures reflecting the temporal directional coherence of the 2D velocity vectors. For example, in [22] or [8], the assumption of a displacement flow in the direction of the maximum downhill slope was considered to study glaciers. This implies that, for a given location, the glacier displacement direction at different dates must be similar.…”

“…The K most expected and the K most unexpected reliable GFS-patterns are finally retained, with K a user defined parameter. 8…”

Attempt of alpine glacier flow modeling based on correlation measurements of high resolution SAR images

“…However, these installations are usually limited by the difficult access to many glacier areas and the expensive maintenance in glacier areas. In the recent years, the remote sensing data acquired by air-borne or space-borne sensors are largely used in complement to in-situ measurements, which allows regular dense measurements of glacier displacement to be performed over large area [2,3,4,5]. The latter is crucial for significant change detection of some physical parameters, as well as for glacier flow model constrain.…”