NDLI: Hyperspectral image segmentation using a new spectral mixture-based binary partition tree representation

Content Provider	IEEE Xplore Digital Library
Author	Veganzones, M.A. Tochon, G. Dalla Mura, M. Plaza, A.J. Chanussot, J.
Copyright Year	2013
Description	Author affiliation: Hyperspectral Comput. Lab., Univ. of Extremadura (UEX), Caceres, Spain (Plaza, A.J.) \|\| GIPSA-Lab., Grenoble-INP, St. Martin d'Hères, France (Veganzones, M.A.; Tochon, G.; Dalla Mura, M.; Chanussot, J.)
Abstract	The Binary Partition Tree (BPT) is a hierarchical region-based representation of an image in a tree structure. BPT allows users to explore the image at different segmentation scales, from fine partitions close to the leaves to coarser partitions close to the root. Often, the tree is pruned so the leaves of the resulting pruned tree conform an optimal partition given some optimality criterion. Here, we propose a novel BPT construction approach and pruning strategy for hyperspectral images based on spectral unmixing concepts. The proposed methodology exploits the local unmixing of the regions to find the partition achieving a global minimum reconstruction error. We successfully tested the proposed approach on the well-known Cuprite hyperspectral image collected by NASA Jet Propulsion Laboratory's Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). This scene is considered as a standard benchmark to validate spectral unmixing algorithms.
Starting Page	245
Ending Page	249
File Size	1588092
Page Count	5
File Format	PDF
ISBN	9781479923410
DOI	10.1109/ICIP.2013.6738051
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-09-15
Publisher Place	Australia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Hyperspectral imaging Image segmentation Merging Image reconstruction Vegetation segmentation Binary Partition Trees hyperspectral images spectral unmixing
Content Type	Text
Resource Type	Article

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