title: Hyperspectral image segmentation using a new spectral unmixing-based binary partition tree representation.
abstract: The binary partition tree (BPT) is a hierarchical region-based representation of an image in a tree structure. The BPT allows users to explore the image at different segmentation scales. Often, the tree is pruned to get a more compact representation and so the remaining nodes conform an optimal partition for some given task. Here, we propose a novel BPT construction approach and pruning strategy for hyperspectral images based on spectral unmixing concepts. Linear spectral unmixing consists of finding the spectral signatures of the materials present in the image (endmembers) and their fractional abundances within each pixel. The proposed methodology exploits the local unmixing of the regions to find the partition achieving a global minimum reconstruction error. Results are presented on real hyperspectral data sets with different contexts and resolutions.
authors.affiliation: Department Image and SignalGIPSA-Laboratory, Grenoble-INP, Saint Martin d'Heres Cedex, France.
authors.forename: Miguel A
authors.initials: MA
authors.lastname: Veganzones
authors.affiliation: Department Image and SignalGIPSA-Laboratory, Grenoble-INP, Saint Martin d'Heres Cedex, France.
authors.forename: Guillaume
authors.initials: G
authors.lastname: Tochon
authors.affiliation: Department Image and SignalGIPSA-Laboratory, Grenoble-INP, Saint Martin d'Heres Cedex, France.
authors.forename: Mauro
authors.initials: M
authors.lastname: Dalla-Mura
authors.affiliation: Hyperspectral Computing Laboratory, University of Extremadura, Cáceres, Spain.
authors.forename: Antonio J
authors.initials: AJ
authors.lastname: Plaza
authors.affiliation: Department Image and SignalGIPSA-Laboratory, Grenoble-INP, Saint Martin d'Heres Cedex, France.
authors.forename: Jocelyn
authors.initials: J
authors.lastname: Chanussot
mesh_terms: D000465:Algorithms; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted; D013057:Spectrum Analysis / Q000379:methods*