Hyperspectral unmixing overview: Geometrical, statistical, and sparse regression-based approaches

JM Bioucas-Dias, A Plaza, N Dobigeon… - IEEE journal of …, 2012 - ieeexplore.ieee.org
Imaging spectrometers measure electromagnetic energy scattered in their instantaneous
field view in hundreds or thousands of spectral channels with higher spectral resolution than …

Remote sensing image processing

G Camps-Valls, D Tuia, L Gómez-Chova, S Jiménez… - 2011 - Springer
Earth observation is the field of science concerned with the problem of monitoring and
modeling the processes on the Earth surface and their interaction with the atmosphere. The …

Hyperspectral image segmentation using a new spectral unmixing-based binary partition tree representation

MA Veganzones, G Tochon… - … on Image Processing, 2014 - ieeexplore.ieee.org
The binary partition tree (BPT) is a hierarchical region-based representation of an image in a
tree structure. The BPT allows users to explore the image at different segmentation scales …

On endmember identification in hyperspectral images without pure pixels: A comparison of algorithms

J Plaza, EMT Hendrix, I García, G Martín… - Journal of Mathematical …, 2012 - Springer
Hyperspectral imaging is an active area of research in Earth and planetary observation. One
of the most important techniques for analyzing hyperspectral images is spectral unmixing, in …

[HTML][HTML] Unsupervised ore/waste classification on open-cut mine faces using close-range hyperspectral data

L Windrim, A Melkumyan, RJ Murphy, A Chlingaryan… - Geoscience …, 2023 - Elsevier
The remote map** of minerals and discrimination of ore and waste on surfaces are
important tasks for geological applications such as those in mining. Such tasks have …

An active contour model based on fused texture features for image segmentation

Q Wu, Y Gan, B Lin, Q Zhang, H Chang - Neurocomputing, 2015 - Elsevier
Texture image segmentation plays an important role in various computer vision tasks. In this
paper, a convex texture image segmentation model is proposed. First, the texture features of …

Análisis de imágenes hiperespectrales

A Roman-Gonzalez, NI Vargas-Cuentas - Revista Ingenieria & …, 2013 - hal.science
Résumé In this paper we present an overview of hyperspectral imagery, its definition, its
creation and acquisition through the basic elements of a remote sensing system, the …

Ensemble learning in hyperspectral image classification: Toward selecting a favorable bias-variance tradeoff

A Merentitis, C Debes… - IEEE Journal of Selected …, 2014 - ieeexplore.ieee.org
Automated classification of hyperspectral images is a fast growing field with numerous
applications in the areas of security and surveillance, agriculture, urban management, and …

Random projection depth for multivariate mathematical morphology

S Velasco-Forero, J Angulo - IEEE Journal of Selected Topics …, 2012 - ieeexplore.ieee.org
The open problem of the generalization of mathematical morphology to vector images is
handled in this paper using the paradigm of depth functions. Statistical depth functions …

Discrimination of schizophrenia auditory hallucinators by machine learning of resting-state functional MRI

D Chyzhyk, M Graña, D Öngür… - International journal of …, 2015 - World Scientific
Auditory hallucinations (AH) are a symptom that is most often associated with schizophrenia,
but patients with other neuropsychiatric conditions, and even a small percentage of healthy …