Title :
Endmember Variability in Hyperspectral Analysis: Addressing Spectral Variability During Spectral Unmixing
Author :
Zare, Alina ; Ho, K.C.
Author_Institution :
Electr. & Comput. Eng., Univ. of Missouri, Columbia, MO, USA
Abstract :
Variable illumination and environmental, atmospheric, and temporal conditions cause the measured spectral signature for a material to vary within hyperspectral imagery. By ignoring these variations, errors are introduced and propagated throughout hyperspectral image analysis. To develop accurate spectral unmixing and endmember estimation methods, a number of approaches that account for spectral variability have been developed. This article motivates and provides a review for methods that account for spectral variability during hyperspectral unmixing and endmember estimation and a discussion on topics for future work in this area.
Keywords :
geophysical image processing; support vector machines; endmember estimation methods; endmember variability; hyperspectral image analysis; hyperspectral unmixing; spectral variability; support vector machines; Atmospheric measurements; Estimation; Hyperspectral imaging; Lighting; Materials; Support vector machines;
Journal_Title :
Signal Processing Magazine, IEEE
DOI :
10.1109/MSP.2013.2279177