Hierarchical analysis of remote sensing data: morphological attribute profiles and binary partition trees

  • Authors:

  • Jon Atli Benediktsson;Lorenzo Bruzzone;Jocelyn Chanussot;Mauro Dalla Mura;Philippe Salembier;Silvia Valero

  • Affiliations:

  • Faculty of Electrical and Computer Engineering, University of Iceland, Reykjavik, Iceland;Department of Information Engineering and Computer Science, University of Trento, Trento, Italy;GIPSA-Lab, Grenoble Institute of Technology, France;Faculty of Electrical and Computer Engineering, University of Iceland, Reykjavik, Iceland and Department of Information Engineering and Computer Science, University of Trento, Trento, Italy;Technical University of Catalonia (UPC), Barcelona, Catalonia, Spain;GIPSA-Lab, Grenoble Institute of Technology, France and Technical University of Catalonia (UPC), Barcelona, Catalonia, Spain

  • Venue:
  • ISMM'11 Proceedings of the 10th international conference on Mathematical morphology and its applications to image and signal processing
  • Year:
  • 2011

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Abstract

The new generation of very high resolution sensors in airborne or satellite remote sensing open the door to countless new applications with a high societal impact. In order to bridge the gap between the potential offered by these new sensors and the needs of the end-users to actually face tomorrow's challenges, advanced image processing methods need to be designed. In this paper we discuss two of the most promising strategies aiming at a hierarchical description and analysis of remote sensing data, namely the Extended Attribute Profiles (EAP) and the Binary Partition Trees (BPT). The EAP computes for each pixel a vector of attributes providing a local multiscale representation of the information and hence leading to a fine description of the local structures of the image. Using different attributes allows to address different contexts or applications. The BPTs provide a complete hierarchical description of the image, from the pixels (the leaves) to larger regions as the merging process goes on. The pruning of the tree provides a partition of the image and can address various goals (segmentation, object extraction, classification). The EAP and BPT approaches are used in experiments and the obtained results demonstrate their importance.