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ICASSP
2011
IEEE

Robust hyperspectral signal unmixing in the presence of correlated noise

8 years 10 months ago
Robust hyperspectral signal unmixing in the presence of correlated noise
Hyperspectral imaging analysis aims at the estimation of the number of constituent substances, known as endmembers, their spectral signatures as well as their abundance fractions . Due to the nature of hyperspectral sensors, output data is mostly associated with correlated noise rather than with the white Gaussian noise considered in most of the analysis. In the presence of correlated noise, estimation of dimensionality with the assumption of white noise is associated with considerable error. This error in the very first step will be propagated to the next steps and fully invalidate the unmixing process. On the other hand, existing methods which consider a correlated noise are lacking in robustness to noise. A Whitened Noiseless Code-length method (WNCLM) is presented for hyperspectral signals dimension estimation and unmixing in the presence of spectrally or spatially correlated noise. Variance and correlation coefficients are calculated to estimate the noise correlation matrix. Th...
Masoud Farzam, Soosan Beheshti
Added 20 Aug 2011
Updated 20 Aug 2011
Type Journal
Year 2011
Where ICASSP
Authors Masoud Farzam, Soosan Beheshti
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