Study of Binary Partition Tree Pruning Techniques for Polarimetric SAR images Philippe Salembier ⋆ Technical University of Catalonia, Barcelona, Spain <philippe.salembier@upc.edu> Abstract. This paper investigates several pruning techniques applied on Binary Partition Trees (BPTs) and their usefulness for low-level pro- cessing of PolSAR images. BPTs group pixels to form homogeneous re- gions, which are hierarchically structured by inclusion in a binary tree. They provide multiple resolutions of description and easy access to sub- sets of regions. Once constructed, BPTs can be used for a large number of applications. Many of these applications consist in populating the tree with a specific feature and in applying a graph-cut called pruning to ex- tract a partition of the space. In this paper, different pruning examples involving the optimization of a global criterion are discussed and ana- lyzed in the context of PolSAR images for segmentation. Initial experi- ments are also reported on the use of Minkowski norms in the definition of the optimization criterion. Keywords: Binary Partition Tree, PolSAR, graph-cut, pruning, speckle noise, segmentation. 1 Introduction The application of Binary Partition Trees (BPTs) [18] for remote sensing appli- cations such as Polarimetric SAR (PolSAR) [2] and hyperspectral images [20, 21] is currently gaining interest. BPTs are hierarchical region-based representations in which pixels are grouped by similarity. Their construction is often based on an iterative region-merging algorithm: starting from an initial partition, the pair of most similar neighboring regions is iteratively merged until one region rep- resenting the entire image support is obtained. The BPT essentially stores the complete merging sequence in a binary tree structure. Once constructed, BPTs can be used for a large number of tasks including image filtering with connected operators, segmentation, object detection or classification [18, 3]. Many of these tasks involve the extraction of a partition from the BPT through a graph cut. In this paper, we focus on low level PolSAR image processing tasks. We study in particular the interest of a specific graph cut called pruning in this context. ⋆ This work has been developed in the framework of the project BIGGRAPH- TEC2013-43935-R, financed by the Spanish Ministerio de Econom´ ıa y Competi- tividad and the European Regional Development Fund (ERDF).