Filtering and segmentation of polarimetric SAR images with Binary Partition Trees

Alonso-González, Alberto; López-Martínez, Carlos; Salembier, Philippe

doi:10.1109/igarss.2010.5653466

Cited by 16 publications

(16 citation statements)

References 3 publications

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“…Furthermore, the mentioned applications are based on similarity measures or distances over the covariance matrix space, as in the case of the proposed technique, making it a natural preprocessing stage as it is based on parallel concepts. For Binary Partition Tree (BPT) [31] based PolSAR speckle filtering and segmentation [15,32] an initial 3 × 3 multilook filter is applied for this purpose. However, this initial step implies a small spatial resolution loss, as seen previously.…”

Section: Resultsmentioning

confidence: 99%

Bilateral Distance Based Filtering for Polarimetric SAR Data

et al. 2013

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This paper introduces a non-linear Polarimetric SAR data filtering approach able to preserve the edges and small details of the data. It is based on exploiting the data locality in both, the spatial and the polarimetric domains, in order to avoid mixing heterogeneous samples of the data. A weighted average is performed over a given window favoring pixel values that are close on both domains. The filtering technique is based on a modified bilateral filtering, which is defined in terms of spatial and polarimetric distances. These distances encapsulate all the knowledge in both domains for an adaptation to the data structure. Finally, the proposed technique is employed to process a real RADARSAT-2 dataset.

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Section: Resultsmentioning

confidence: 99%

Bilateral Distance Based Filtering for Polarimetric SAR Data

et al. 2013

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“…The BPT representation can be employed to process PolSAR images, as described in [14]- [16]. In these publications, the traditional 8-connectivity was employed, and the polarimetric covariance matrix (2) was used as a region model.…”

Section: Polsar Time Series Bptmentioning

confidence: 99%

PolSAR Time Series Processing With Binary Partition Trees

Alonso-González

López-Martínez

Salembier

2014

IEEE Trans. Geosci. Remote Sensing

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Abstract-This paper deals with the processing of polarimetric synthetic aperture radar (SAR) time series. Different approaches to deal with the temporal dimension of the data are considered, which are derived from different target characterizations in this dimension. These approaches are the basis for defining two different binary partition tree (BPT) structures that are employed for SAR polarimetry (PolSAR) data processing. Once constructed, the BPT is processed by a tree pruning, producing a set of spatiotemporal homogeneous regions, and estimating the polarimetric response within them. It is demonstrated that the proposed technique preserves the PolSAR information in the spatial and the temporal domains without introducing bias nor distortion. Additionally, the evolution of the data in the temporal dimension is also analyzed, and techniques to obtain BPT-based scene change maps are defined. Finally, the proposed techniques are employed to process two real RADARSAT-2 data sets.

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“…This constraint justify the use of i ' and i 2 norms in the standard one dimensional case, the bests well-known algorithms using costs functions associated with these norms being respectively some variants of the Wiener-like ( [1], [2], [3], [4], among others) and median-based ( [5], [6], [7], among others) filtering strategies.…”

Section: Introductionmentioning

confidence: 99%

“…Standard methods for filtering remote sensing data are mainly based on the minimization of i 2 and i ' error norm cost functions, see [1], [2], [3], [4], [5], [6], [7], among others.…”

Section: Introductionmentioning

confidence: 99%