Classification of hyperspectral images by tensor modeling and additive morphological decomposition

Pixel-wise classification in high-dimensional multivariate images is investigated. The proposed method deals with the joint use of spectral and spatial information provided in hyperspectral images. Additive morphological decomposition (AMD) based on morphological operators is proposed. AMD defines a...

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Vydáno v:	Pattern recognition Ročník 46; číslo 2; s. 566 - 577
Hlavní autoři:	Velasco-Forero, Santiago, Angulo, Jesus
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Kidlington Elsevier Ltd 01.02.2013 Elsevier
Témata:	Additives Algorithms Applied sciences Artificial intelligence Classification Computer Science Computer science; control theory; systems Decomposition Engineering Sciences Exact sciences and technology Hyperspectral images Information, signal and communications theory Mathematical analysis Mathematical morphology Pattern recognition Pattern recognition. Digital image processing. Computational geometry Pixelwise classification Signal and Image processing Signal processing Spectra Telecommunications and information theory Tensor modeling Tensors Hyperspectral images Pixelwise classification Mathematical morphology Tensor modeling Performance evaluation Pixelwise Pattern recognition Algorithm Modeling Statistical method Hyperspectral imaging sensor Dimension reduction Multiscale method Tensor calculus Principal component analysis Hyperspectral Morphology
ISSN:	0031-3203, 1873-5142
On-line přístup:	Získat plný text
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