On the Use of a Hybrid Approach to Contrast Endmember Induction Algorithms View Full Text


Ontology type: schema:Chapter      Open Access: True


Chapter Info

DATE

2010

AUTHORS

Miguel A. Veganzones , Carmen Hernández

ABSTRACT

In 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... »

PAGES

69-76

Book

TITLE

Hybrid Artificial Intelligence Systems

ISBN

978-3-642-13802-7
978-3-642-13803-4

Author Affiliations

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-642-13803-4_9

DOI

http://dx.doi.org/10.1007/978-3-642-13803-4_9

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1015846327


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