Ontology type: schema:Chapter Open Access: True
2010
AUTHORSMiguel A. Veganzones , Carmen Hernández
ABSTRACTIn remote sensing hyperspectral image processing, identifying the constituent spectra (endmembers) of the materials in the image is a key procedure for further analysis. The contrast between Endmember Inductions Algorithms (EIAs) is a delicate issue, because there is a shortage of validation images with accurate ground truth information, and the induced endmembers may not correspond to any know material, because of illumination and atmospheric effects. In this paper we propose a hybrid validation method, composed on a simulation module which generates the validation images from stochastic models and evaluates the EIA through Content Based Image Retrieval (CBIR) on the database of simulated hyperspectral images. We demonstrate the approach with two EIA selected from the literature. More... »
PAGES69-76
Hybrid Artificial Intelligence Systems
ISBN
978-3-642-13802-7
978-3-642-13803-4
http://scigraph.springernature.com/pub.10.1007/978-3-642-13803-4_9
DOIhttp://dx.doi.org/10.1007/978-3-642-13803-4_9
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