Results 151 to 160 of about 6,103 (201)

Spectral unmixing

International Journal of Remote Sensing, 2012
Satellite imagery is formed by finite digital numbers representing a specific location of ground surface in which each matrix element is denominated as a picture element or pixel. The pixels represent the sensor measurements of spectral radiance. The radiance recorded in the satellite images is then an integrated sum of the radiances of all targets ...
Carmen Quintano, Alfonso Fernández-Manso, Yosio E. Shimabukuro, Gabriel Pereira   +3 more
openaire   +1 more source

Spatial–spectral preprocessing for spectral unmixing

International Journal of Remote Sensing, 2018
Most techniques available in the endmember extraction rely on exploiting the spectral information of the data alone.
Yang Yan, Wenshen Hua, Xun Liu, Zihao Cui, Dongmei Diao   +4 more
openaire   +1 more source

Spatially informed spectral unmixing

2015 7th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2015
Spectral unmixing methods have traditionally relied on the plethora of information in the spectral domain to resolve subpixel components. Several new methods have utilised the spatial information contained within the hyperspectral image, however these are limited to the spatial resolution of the sensor.
Daniel L. Bongiorno, Adam J. Fairley, Stefan B. Williams   +2 more
openaire   +1 more source

Spectral Unmixing Using Deep Convolutional Encoder-Decoder

2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, 2021
In this paper, we introduce ‘Unmixing Deep Image Prior’ (UnDIP), a deep learning-based technique for the linear hyperspectral unmixing problem. The proposed method contains two steps. First, the endmembers are extracted using a geometric endmember extraction method, i.e. a simplex volume maximization in a subspace of the dataset.
Rasti, B., Koirala, B., Scheunders, P., Ghamisi, P.   +3 more
openaire   +3 more sources

Optimal linear spectral unmixing

IEEE Transactions on Geoscience and Remote Sensing, 1999
The optimal estimate of ground cover components of a linearly mixed spectral pixel in remote-sensing imagery is investigated. The problem is formulated as two consecutive constrained least-squares (LS) problems: the first problem concerns the estimation of the end-member spectra (EMS), and the second concerns the estimate, within each mixed pixel, of ...
Y.H. Hu, H.B. Lee, F.L. Scarpace
openaire   +1 more source

Iterative spectral unmixing (ISU)

International Journal of Remote Sensing, 1999
Spectral unmixing techniques strive to find proportions of end-members within a pixel from the observed mixed pixel spectrum and a number of pure end-member spectra of known composition. The outcomes of such analysis are fraction (abundance) images for the selected (pure) end-members and a root mean square (RMS) error estimate representing the ...
openaire   +2 more sources

Spectral unmixing using linear unmixing under spatial autocorrelation constraints

2010 IEEE International Geoscience and Remote Sensing Symposium, 2010
This paper presents a spectral unmixing approach that is implemented using linear unminxing method by a genetic algorithm. The unmixing is constrained not only by the negativity and sum-to-one of the abundances of endmembers at each pixel but also by the spatial autocorrelation of their abundances among eight neighbor pixels.
Xianfeng Song, Xiaoguang Jiang, Xiaoping Rui   +2 more
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Spectral unmixing using distance geometry

2011 3rd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2011
In this paper, we present a new method for solving the spectral unmixing problem which uses only the spectral distances between the data points and the endmembers. This method is obtained by reformulating every step of the recently developed SPU algorithm entirely in distance geometry, yielding a recursive algorithm based on the geometrical properties ...
Heylen, Rob, Scheunders, Paul
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Particle filter for spectral unmixing

2011 8th International Conference on Electrical Engineering, Computing Science and Automatic Control, 2011
The paper addresses the problem of identification of fluorescent molecules, or fluorophores, in biological samples obtained from time-resolved fluorescence microscopy. The contribution of this work is an algorithm, based on particle filter optimization, that solves the spectral unmixing problem for more than two fluorophores even when they present ...
Omar Gutierrez-Navarro, Edgar R. Arce-Santana, Daniel U. Campos-Delgado, Martin O. Mendez, Javier A. Jo   +4 more
openaire   +1 more source