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Conference papers
Morphological Processing of Hyperspectral Images Using Kriging-Based Supervised Ordering
Abstract : A novel approach for vectorial ordering is introduced in this paper. The generic framework is based on a supervised learning formulation which leads to reduced orderings. A training set for the background and another training set for the foreground are needed as well as a supervised method to construct the ordering mapping. In particular, we consider here a kriging-based vectorial ordering. This supervised ordering may then used for the extension of mathematical morphology to vectorial images. Application of morphological processing to hyperspectral image illustrates the performance of proposal operators.
Keywords :
Generic frameworks
Hyper-spectral images
Hyperspectral imagery
Kriging
Learning formulation
Morphological processing
Training sets
Vectorial images
Image processing
Imaging systems
Independent component analysis
Interpolation
Mathematical operators
Remote sensing
Supervised learning
Mathematical morphology
https://hal-mines-paristech.archives-ouvertes.fr/hal-00834434
Contributor : Bibliothèque MINES ParisTech Connect in order to contact the contributor
Submitted on : Saturday, June 15, 2013 - 8:51:05 AM
Last modification on : Wednesday, November 17, 2021 - 12:27:09 PM
Contributor : Bibliothèque MINES ParisTech Connect in order to contact the contributor
Submitted on : Saturday, June 15, 2013 - 8:51:05 AM
Last modification on : Wednesday, November 17, 2021 - 12:27:09 PM