An adaptive surrogate-assisted endmember extraction framework based on intelligent optimization algorithms for hyperspectral remote sensing images
As the foremost step of spectral unmixing, endmember extraction has been one of the most
challenging techniques in the spectral unmixing processing due to the mixing of pixels and …
challenging techniques in the spectral unmixing processing due to the mixing of pixels and …
A fast endmember extraction algorithm based on Gram determinant
In the field of endmember extraction, most methods involve calculating the volume of
simplex in high-dimensional space. Two different simplex volume formulas are used in these …
simplex in high-dimensional space. Two different simplex volume formulas are used in these …
Lattice independent component analysis feature selection on diffusion weighted imaging for Alzheimer's disease classification
Diffusion weighted imaging (DWI) provides information on the diffusion of water molecules
which can be useful to determine structural properties in the brain. Specifically, fractional …
which can be useful to determine structural properties in the brain. Specifically, fractional …
Hybrid sparse linear and lattice method for hyperspectral image unmixing
Linear spectral unmixing aims to estimate the fractional abundances of spectral signatures
in each pixel. The Linear Mixing Model (LMM) of hyperspectral images assumes that pixel …
in each pixel. The Linear Mixing Model (LMM) of hyperspectral images assumes that pixel …
[PDF][PDF] Contributions to hyperspectral image processing from Lattice Computing and Computational Intelligence
MAV Bodón - 2012 - researchgate.net
The main material on which this Thesis works are remote sensing hyperspectral images. It is
expected of the deployment of hyperspectral imaging sensors to improve our ability for …
expected of the deployment of hyperspectral imaging sensors to improve our ability for …
Hybrid computational methods for hyperspectral image analysis
In this paper we provide a brief review of recent advances in computational methods for
hyperspectral image analysis with emphasis in hybrid approaches. Hyperspectral imagery …
hyperspectral image analysis with emphasis in hybrid approaches. Hyperspectral imagery …
Greedy sparsification WM algorithm for endmember induction in hyperspectral images
Abstract The Linear Mixing Model (LMM) of hyperspectral images asumes that pixel spectra
are affine combinations of basic spectral signatures, called endmembers, which are the …
are affine combinations of basic spectral signatures, called endmembers, which are the …
[PDF][PDF] Lattice Computing and Hyperspectral Image Processing for Human Detection and Identification
IM Bailón - 2014 - ehu.eus
The thesis has a main application topic, directly related to face based biometric
identification, which proceeds in two substantial steps, first face localization in the image …
identification, which proceeds in two substantial steps, first face localization in the image …
Bioinspired and knowledge based techniques and applications
This special issue covers some recent advances on bioinspired and knowledge based
techniques with some emphasis on applications to the medical domain, specifically in …
techniques with some emphasis on applications to the medical domain, specifically in …
Sparse unmixing via WM algorithm for hyperspectral images
Spectral unmixing aims to estimate the fractional abundances of spectral signatures in each
pixel. The Linear Mixing Model (LMM) of hyperspectral images assumes that pixel spectra …
pixel. The Linear Mixing Model (LMM) of hyperspectral images assumes that pixel spectra …