Estimation of signal subspace on hyperspectral data

José M. Bioucas-Dias; José M. P. Nascimento

doi:10.1117/12.620061

18 October 2005 Estimation of signal subspace on hyperspectral data

José M. Bioucas-Dias, José M. P. Nascimento

Proceedings Volume 5982, Image and Signal Processing for Remote Sensing XI; 59820L (2005) https://doi.org/10.1117/12.620061
Event: SPIE Remote Sensing, 2005, Bruges, Belgium

Abstract

Dimensionality reduction plays a crucial role in many hyperspectral data processing and analysis algorithms. This paper proposes a new mean squared error based approach to determine the signal subspace in hyperspectral imagery. The method first estimates the signal and noise correlations matrices, then it selects the subset of eigenvalues that best represents the signal subspace in the least square sense. The effectiveness of the proposed method is illustrated using simulated and real hyperspectral images.

Citation Download Citation

José M. Bioucas-Dias and José M. P. Nascimento "Estimation of signal subspace on hyperspectral data", Proc. SPIE 5982, Image and Signal Processing for Remote Sensing XI, 59820L (18 October 2005); https://doi.org/10.1117/12.620061

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