@article {aSalembier18, title = {Ship Detection in SAR Images Based on Maxtree Representation and Graph Signal Processing}, journal = {IEEE Transactions on Geoscience and Remote Sensing}, volume = {57}, year = {2019}, month = {05/2019}, pages = {2709 - 2724}, author = {Salembier, P. and Liesegang, S. and L{\'o}pez-Mart{\'\i}nez, C.} } @conference {cSalembier14, title = {Low-level processing of PolSAR images with binary partition trees}, booktitle = {IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2014}, year = {2014}, month = {07/2014}, publisher = {IEEE}, organization = {IEEE}, address = {Quebec, Canada}, abstract = {

This paper discusses the interest of Binary Partition Trees (BPTs) and the usefulness of graph cuts for low-level processing of PolSAR images. BPTs group pixels to form homogeneous regions, which are hierarchically structured by inclusion in a tree. They provide multiple resolutions of description and easy access to subsets of regions. Once constructed, BPTs can be used for many applications including filtering, segmentation, classification and object detection. Many processing strategies consist in populating the tree with a specific feature and in applying a graph-cut called pruning. Different graph-cuts are discussed and analyzed in the context of PolSAR images for speckle filtering and segmentation.

}, author = {Salembier, P. and S. Foucher and L{\'o}pez-Mart{\'\i}nez, C.} } @conference {cAlonso-Gonzalez14, title = {Multidimensional SAR Data Analysis Based on Binary Partition Trees and the Covariance Matrix Geometry}, booktitle = {International Radar Conference 2014}, year = {2014}, month = {10/2014}, publisher = {SEE}, organization = {SEE}, address = {Lille, France}, abstract = {

In this paper, we propose the use of the Binary Partition Tree (BPT) as a region-based and multi-scale image representation to process multidimensional SAR data, with special emphasis on polarimetric SAR data. We also show that this approach could be extended to other types of remote sensing imaging technologies, such as hyperspatial imagery. The Binary Partition Tree contains a lot of information about the image structure at different detail levels. At the same time, this structure represents a convenient vehicle to exploit both the statistical properties, as well as the geometric properties of the multidimensional SAR data given by the covariance matrix. The BPT construction process and its exploitation for PolSAR and temporal data information estimation is analyzed in this work. In particular, this work focuses on the speckle noise filtering problem and the temporal characterization of the image dynamics. Results with real data are presented to illustrate the capabilities of the BPT processing approach, specially to maintain the spatial resolution and the small details of the image.

}, author = {Alonso-Gonz{\'a}lez, A. and L{\'o}pez-Mart{\'\i}nez, C. and Salembier, P.} } @article {aAlonso-Gonzalez, title = {PolSAR Time Series Processing with Binary Partition Trees}, journal = {IEEE Transactions on Geoscience and Remote Sensing}, volume = {52}, year = {2014}, month = {06/2014}, pages = {3553 {\textendash} 3567}, 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.

}, issn = {0196-2892}, doi = {10.1109/TGRS.2013.2273664}, author = {Alonso-Gonz{\'a}lez, A. and L{\'o}pez-Mart{\'\i}nez, C. and Salembier, P.} } @article {aAlonso-Gonzalez13a, title = {Bilateral Distance Based Filtering for Polarimetric SAR Data}, journal = {Remote Sensing}, volume = {5}, year = {2013}, month = {10/2013}, pages = {5620-5641}, abstract = {

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.

}, issn = {2072-4292}, doi = {10.3390/rs5115620}, author = {Alonso-Gonz{\'a}lez, A. and L{\'o}pez-Mart{\'\i}nez, C. and Salembier, P. and X. Deng} } @conference {cAlonso-Gonzalez13, title = {PolSAR time series processing and analysis based on Binary Partition Trees}, booktitle = {PoLinSAR 2013 Workshop}, year = {2013}, address = {Frascati (Rome), Italy}, author = {Alonso-Gonz{\'a}lez, A. and L{\'o}pez-Mart{\'\i}nez, C. and Salembier, P.} } @article {aAlonso-Gonzalez13, title = {Processing Multidimensional SAR and Hyperspectral Images With Binary Partition Tree}, journal = {Proceedings of the IEEE}, volume = {101}, year = {2013}, month = {March, 2013}, pages = {723 - 747}, chapter = {723 - 747}, abstract = {

The current increase of spatial as well as spectral resolutions of modern remote sensing sensors represents a real opportunity for many practical applications but also generates important challenges in terms of image processing. In particular, the spatial correlation between pixels and/or the spectral correlation between spectral bands of a given pixel cannot be ignored. The traditional pixel-based representation of images does not facilitate the handling of these correlations.

In this paper, we discuss the interest of a particular hierarchical region-based representation of images based on binary partition tree (BPT). This representation approach is very flexible as it can be applied to any type of image. Here both optical and radar images will be discussed. Moreover, once the image representation is computed, it can be used for many different applications. Filtering, segmentation, and classification will be detailed in this paper. In all cases, the interest of the BPT representation over the classical pixel-based representation will be highlighted.

}, doi = {10.1109/JPROC.2012.2205209}, author = {Alonso-Gonz{\'a}lez, A. and Valero, S. and Chanussot, J. and L{\'o}pez-Mart{\'\i}nez, C. and Salembier, P.} } @article {aAlonso-Gonzalez12, title = {Filtering and Segmentation of Polarimetric SAR Data Based on Binary Partition Trees}, journal = {IEEE transactions on geoscience and remote sensing}, volume = {50}, year = {2012}, pages = {593{\textendash}605}, abstract = {

In this paper,we propose the use of binary partition trees (BPT) to introduce a novel region-based and multi-scale polarimetric SAR (PolSAR) data representation. The BPT structure represents homogeneous regions in the data at different detail levels. The construction process of the BPT is based, firstly, on a region model able to represent the homogeneous areas, and, secondly, on a dissimilarity measure in order to identify similar areas and define the merging sequence. Depending on the final application, a BPT pruning strategy needs to be introduced. In this paper, we focus on the application of BPT PolSAR data representation for speckle noise filtering and data segmentation on the basis of the Gaussian hypothesis, where the average covariance or coherency matrices are considered as a region model. We introduce and quantitatively analyze different dissimilarity measures. In this case, and with the objective to be sensitive to the complete polarimetric information under the Gaussian hypothesis, dissimilarity measures considering the complete covariance or coherency matrices are employed. When confronted to PolSAR speckle filtering, two pruning strategies are detailed and evaluated. As presented, the BPT PolSAR speckle filter defined filters data according to the complete polarimetric information. As shown, this novel filtering approach is able to achieve very strong filtering while preserving the spatial resolution and the polarimetric information. Finally, the BPT representation structure is employed for high spatial resolution image segmentation applied to coastline detection. The analyses detailed in this work are based on simulated, as well as on real PolSAR data acquired by the ESAR system of DLR and the RADARSAT-2 system.

}, issn = {0196-2892}, doi = {10.1109/TGRS.2011.2160647}, author = {Alonso-Gonz{\'a}lez, A. and L{\'o}pez-Mart{\'\i}nez, C. and Salembier, P.} } @conference {cAlonso-Gonzalez12a, title = {Temporal polsar image series exploitation with binary partition trees}, booktitle = {IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2012}, year = {2012}, address = {Munich, Germany}, author = {Alonso-Gonz{\'a}lez, A. and L{\'o}pez-Mart{\'\i}nez, C. and Salembier, P.} } @conference {cAlonso-Gonzalez12, title = {Variable local weight filtering for polsar data speckle noise reduction}, booktitle = {IEEE International Geoscience and Remote Sensing Symposium, IGARSS{\textquoteright}2012}, year = {2012}, address = {Munich, Germany}, author = {Alonso-Gonz{\'a}lez, A. and L{\'o}pez-Mart{\'\i}nez, C. and Salembier, P.} } @conference {cAlonso-Gonzalez11a, title = {Binary partition tree as a polarimetric SAR data representation in the space-time domain}, booktitle = {IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2011}, year = {2011}, pages = {3819{\textendash}3822}, address = {Vanouver, Canada}, isbn = {978-1-4577-1005-6}, doi = {10.1109/IGARSS.2011.6050063}, url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6050063}, author = {Alonso-Gonz{\'a}lez, A. and L{\'o}pez-Mart{\'\i}nez, C. and Salembier, P.} } @article {aTello11, title = {Edge enhancement algorithm based on the wavelet transform for automatic edge detection in SAR images}, journal = {IEEE transactions on geoscience and remote sensing}, volume = {49}, number = {1}, year = {2011}, pages = {222{\textendash}235}, issn = {0196-2892}, doi = {10.1109/TGRS.2010.2052814}, url = {http://hdl.handle.net/2117/11057}, author = {Tello, M. and L{\'o}pez-Mart{\'\i}nez, C. and Mallorqui, J.J. and Salembier, P.} } @conference {cAlonso-Gonzalez11, title = {PolSAR speckle filtering and segmentation based on binary partition tree representation}, booktitle = {5th International Workshop on Science and Applications of SAR Polarimetry and Polarimetric Interferometry, PolInSAR 2011}, year = {2011}, pages = {1{\textendash}19}, address = {Frascati (Rome), Italy}, url = {http://cataleg.upc.edu/record=b1233548~S1*cat}, author = {Alonso-Gonz{\'a}lez, A. and L{\'o}pez-Mart{\'\i}nez, C. and Salembier, P.} } @conference {cAlonso-Gonzalez10, title = {Filtering and segmentation of polarimetric SAR images with binary partition trees}, booktitle = {IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2010}, year = {2010}, pages = {4043{\textendash}4046}, address = {Honolulu, USA}, isbn = {978-1-4244-9564-1}, doi = {10.1109/IGARSS.2010.5653466}, url = {http://cataleg.upc.edu/record=b1167223~S1*cat}, author = {Alonso-Gonz{\'a}lez, A. and L{\'o}pez-Mart{\'\i}nez, C. and Salembier, P.} }