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2010
IEEE

Comparison of merging orders and pruning strategies for Binary Partition Tree in hyperspectral data

8 years 5 months ago
Comparison of merging orders and pruning strategies for Binary Partition Tree in hyperspectral data
Hyperspectral imaging segmentation has been an active research area over the past few years. Despite the growing interest, some factors such as high spectrum variability are still significant issues. In this work, we propose to deal with segmentation through the use of Binary Partition Trees (BPTs). BPTs are suggested as a new representation of hyperspectral data representation generated by a merging process. Different hyperspectral region models and similarity metrics defining the merging orders are presented and analyzed. The resulting merging sequence is stored in a BPT structure which enables image regions to be represented at different resolution levels. The segmentation is performed through an intelligent pruning of the BPT, that selects regions to form the final partition. Experimental results on two hyperspectral data sets have allowed us to compare different merging orders and pruning strategies demonstrating the encouraging performances of BPT-based representation.
Silvia Valero, Philippe Salembier, Jocelyn Chanuss
Added 12 Feb 2011
Updated 12 Feb 2011
Type Journal
Year 2010
Where ICIP
Authors Silvia Valero, Philippe Salembier, Jocelyn Chanussot
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