A Change Detector Based on an Optimization With Polarimetric SAR Imagery

作者：Marino Armando^*; Hajnsek Irena

来源：IEEE Transactions on Geoscience and Remote Sensing, 2014, 52(8): 4781-4798.

DOI：10.1109/TGRS.2013.2284510

• Change detection
• equiscattering mechanisms (ESMs)
• polarimetry
• synthetic aperture radar

The possibility to detect changes in land cover with remote sensing is particularly valuable considering the current availability of long time series of data. Synthetic Aperture Radar (SAR) can play an important role in this context since it can acquire complete time series without limitations of cloud cover. Additionally, polarimetry has the potential to improve significantly the detection capability, allowing the discrimination between different polarimetric targets. This paper is focused on developing two new methodologies for testing the stability of observed targets (i.e., equiscattering-mechanism hypothesis) and change detection. Both the algorithms adopt a Lagrange optimization, which can be performed with two eigenproblems. Interestingly, the two optimizations share the same eigenvectors. Three statistical tests are proposed to set the threshold for the change detector. Two of them are mostly aimed at point targets, and one is more suited for distributed targets. All the algorithms and procedures developed in this paper are tested on two different quad-polarimetric data sets acquired by the Experimental-SAR (E-SAR) German Aerospace Center (DLR) system in L-band (SARTOM 2006 and AGRISAR 2006 campaigns). The data sets are accompanied by ground surveys. The detectors are able to identify targets and areas with validated changes or showing clear differences in the images. The theoretical probability density function exploited to model the optimum ratio fits adequately the data and therefore has been used for the statistical tests. Regarding the output of the tests, two of them provided good results, while one needs more care and adjustments.

• 出版日期2014-8