IEEE Trans Image Process - Hyperspectral image representation and processing with binary partition trees.

Tópicos

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Resumo

The optimal exploitation of the information provided by hyperspectral images requires the development of advanced image-processing tools. This paper proposes the construction and the processing of a new region-based hierarchical hyperspectral image representation relying on the binary partition tree (BPT). This hierarchical region-based representation can be interpreted as a set of hierarchical regions stored in a tree structure. Hence, the BPT succeeds in presenting: 1) the decomposition of the image in terms of coherent regions, and 2) the inclusion relations of the regions in the scene. Based on region-merging techniques, the BPT construction is investigated by studying the hyperspectral region models and the associated similarity metrics. Once the BPT is constructed, the fixed tree structure allows implementing efficient and advanced application-dependent techniques on it. The application-dependent processing of BPT is generally implemented through a specific pruning of the tree. In this paper, a pruning strategy is proposed and discussed in a classification context. Experimental results on various hyperspectral data sets demonstrate the interest and the good performances of the BPT representation.

Resumo Limpo

optim exploit inform provid hyperspectr imag requir develop advanc imageprocess tool paper propos construct process new regionbas hierarch hyperspectr imag represent reli binari partit tree bpt hierarch regionbas represent can interpret set hierarch region store tree structur henc bpt succeed present decomposit imag term coher region inclus relat region scene base regionmerg techniqu bpt construct investig studi hyperspectr region model associ similar metric bpt construct fix tree structur allow implement effici advanc applicationdepend techniqu applicationdepend process bpt general implement specif prune tree paper prune strategi propos discuss classif context experiment result various hyperspectr data set demonstr interest good perform bpt represent

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