IEEE Trans Image Process - Hyperspectral image segmentation using a new spectral unmixing-based binary partition tree representation.

Tópicos

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Resumo

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.

Resumo Limpo

binari partit tree bpt hierarch regionbas represent imag tree structur bpt allow user explor imag differ segment scale often tree prune get compact represent remain node conform optim partit given task propos novel bpt construct approach prune strategi hyperspectr imag base spectral unmix concept linear spectral unmix consist find spectral signatur materi present imag endmemb fraction abund within pixel propos methodolog exploit local unmix region find partit achiev global minimum reconstruct error result present real hyperspectr data set differ context resolut

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