• Corpus ID: 2262092

Application of the Second-Order Statistics for Estimation of the Pure Spectra of Individual Components from the Visible Hyperspectral Images of Their Mixture

@article{Jong2016ApplicationOT,
  title={Application of the Second-Order Statistics for Estimation of the Pure Spectra of Individual Components from the Visible Hyperspectral Images of Their Mixture},
  author={Sung-Ho Jong and Yong-U. Ri and Kye-Ryong Sin},
  journal={ArXiv},
  year={2016},
  volume={abs/1604.03193}
}
The second-order statistics (SOS) can be applied in estimation of the pure spectra of chemical components from the spectrum of their mixture, when SOS seems to be good at estimation of spectral patterns, but their peak directions are opposite in some cases. In this paper, one method for judgment of the peak direction of the pure spectra was proposed, where the base line of the pure spectra was drawn by using their histograms and the peak directions were chosen so as to make all of the pure… 

References

SHOWING 1-10 OF 16 REFERENCES

Blind Source Separation via Generalized Eigenvalue Decomposition

The fact that linear blind source separation can be formulated as a generalized eigenvalue decomposition under the assumptions of non-Gaussian, non-stationary, or non-white independent sources is highlighted.

A blind source separation technique using second-order statistics

A new source separation technique exploiting the time coherence of the source signals is introduced, which relies only on stationary second-order statistics that are based on a joint diagonalization of a set of covariance matrices.

A generalization of blind source separation algorithms for convolutive mixtures based on second-order statistics

A general broadband approach to blind source separation (BSS) for convolutive mixtures based on second-order statistics is presented and constraints are obtained which provide a deeper understanding of the internal permutation problem in traditional narrowband frequency-domain BSS.

A fast second order blind identification method for separation of periodic sources

In this paper a fast method for blind identification of periodic sources is presented. In the well-known second order blind identification method, the information is extracted from instantaneous

Second Order Blind Source Separation techniques (SO-BSS) and their relation to Stochastic Subspace Identification (SSI) algorithm

Work presented in this paper aims at establishing a link between SO-BSS techniques (such as AMUSE and SOBI) and Stochastic Subspace Iteration (SSI) algorithm, which is a well known OMA algorithm.

Second-order blind separation of first- and second-order cyclostationary sources-application to AM, FSK, CPFSK, and deterministic sources

The purpose of this paper is to analyze the behavior and to propose adaptations of the current SO BSS methods for sources that are both FIO and SO cyclostationary and cyclo-ergodic, and an extension for deterministic sources is also proposed.

Convolutive blind separation of non-stationary sources

This work tackles the problem of source separation by explicitly exploiting the nonstationarity of the acoustic sources, and finds an FIR backward model, which generates well separated model sources.

Blind Source Separation Techniques for Decomposing Event-Related Brain Signals

The concept of BSS is reviewed and its usefulness in the context of event-related MEG measurements is demonstrated and an additional grouping of the BSS components reveals interesting structure, that could ultimately be used for gaining a better physiological modeling of the data.

Robust whitening procedure in blind source separation context

An efficient algorithm is presented for robust whitening in the presence of temporally uncorrelated additive noise that may be spatially correlated. This whitening is introduced as a pre-processing