Results 181 to 190 of about 3,939 (225)

Superpixel construction for hyperspectral unmixing

2018 26th European Signal Processing Conference (EUSIPCO), 2018
Spectral unmixing aims to determine the component materials and their associated abundances from mixed pixels in a hyperspectral image. Instead of performing unmixing independently on each pixel, investigating spatial and spectral correlations among pixels can be beneficial to enhance the unmixing performance.
Zeng Li 0001, Jie Chen 0022, Susanto Rahardja   +2 more
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Spatially Adaptive Hyperspectral Unmixing

IEEE Transactions on Geoscience and Remote Sensing, 2011
Spectral unmixing is a common task in hyperspectral data analysis. In order to sufficiently spectrally unmix the data, three key steps must be accomplished: Estimate the number of endmembers (EMs), identify the EMs, and then unmix the data. Several different statistical and geometrical approaches have been developed for all steps of the unmixing ...
Kelly Canham, Ariel Schlamm, Amanda Ziemann, Bill Basener, David W. Messinger   +4 more
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Sparse distributed hyperspectral unmixing

2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2016
Blind hyperspectral unmixing is the task of jointly estimating the spectral signatures of material in a hyperspectral images and their abundances at each pixel. The size of hyperspectral images are usually very large, which may raise difficulties for classical optimization algorithms, due to limited memory of the hardware used.
Jakob Sigurdsson, Magnus O. Ulfarsson, Johannes R. Sveinsson, José M. Bioucas-Dias   +3 more
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On Diverse Noises in Hyperspectral Unmixing

IEEE Transactions on Geoscience and Remote Sensing, 2015
Traditional spectral unmixing methods are usually based on the linear mixture model (LMM) or nonlinear mixture model (NLMM), in which only the additive noise is considered. However, in hyperspectral applications, the additive, multiplicative, and mixed noises play important roles. In this paper, we propose an antinoise model for hyperspectral unmixing.
Chunzhi Li, Xiaohua Chen 0001, Yunliang Jiang   +2 more
openaire   +1 more source

Segmentation-based cNMF for hyperspectral unmixing

2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2017
This paper presents a modification to the cNMF for unmixing where the image is first segmented and the cNMF is applied to individual segments for endmember extraction. Extracted spectral endmembers from individual segments are clustered in endmember classes to describe the entire image. The approach is compared with the global cNMF.
Mohammed Q. Alkhatib, Miguel Velez-Reyes
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Compressed sensing based hyperspectral unmixing

2014 22nd Signal Processing and Communications Applications Conference (SIU), 2014
In hyperspectral images the measured spectra for each pixel can be modeled as convex combination of small number of endmember spectra. Since the measured structure contains only a few of possible responses out of possibly many materials sparsity based convex optimization techniques or compressive sensing can be used for hyperspectral unmixing.
R. Tufan Albayrak, Ali Cafer Gürbüz, Bertan Günyel   +2 more
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Blind hyperspectral unmixing

SPIE Proceedings, 2007
ABSTRACT Hyperspectral unmixing methods aim at the decompositio n of a hyperspectral image in to a collection endmembersignatures, i.e., the radiance or re”ectance of the materials present in the scene, and the correspondent abundancefractions at each pixel in the image.This paper introduces a new unmixing method termed dependent component analysis ...
Nascimento, Jose, Bioucas-Dias, José M.
openaire   +3 more sources

Coupled hyperspectral super-resolution and unmixing

2014 IEEE Geoscience and Remote Sensing Symposium, 2014
The acquired hyperspectral data are always in low resolution in both spatial and spectral domains, which will result in lots of mixed pixels and degrade the detection and recognition performance in civil and military applications. So many super resolution techniques are applied to overcome this limit.
Yongqiang Zhao 0001, Chen Yi, Jingxiang Yang, Jonathan Cheung-Wai Chan   +3 more
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Double Constrained NMF for Hyperspectral Unmixing

IEEE Transactions on Geoscience and Remote Sensing, 2014
Given only the collected hyperspectral data, unmixing aims at obtaining the latent constituent materials and their corresponding fractional abundances. Recently, many nonnegative matrix factorization (NMF)-based algorithms have been developed to deal with this issue.
Lu, Xiaoqiang, Wu, Hao, Yuan, Yuan
openaire   +2 more sources

Robust Sparse Unmixing for Hyperspectral Imagery

IEEE Transactions on Geoscience and Remote Sensing, 2018
A linear sparse unmixing method based on spectral library has been widely used to tackle the hyperspectral unmixing problem, under the assumption that the spectrum of each pixel in the hyperspectral scene can be expressed as a linear combination of pure endmembers in the spectral library.
Dan Wang 0005, Zhenwei Shi 0001, Xinrui Cui   +2 more
openaire   +1 more source