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\iteman{io-port 06040986}
\itemau{Zhan, Xilan; Wu, Bo}
\itemti{A method of spectral mixture analysis based on the Gaussian Markov random field model.}
\itemso{J. Fuzhou Univ., Nat. Sci. 39, No. 1, 60-66 (2011).}
\itemab
Summary: Traditional spectral mixture techniques only considered spectral information and usually ignored the efficient utilization of spatially dependent information. In fact, the phenomenon of spatial dependence can be observed in both remotely sensed images and unmixed abundance images. The spatial dependence is depicted in this paper by a Gaussian Markov random field (GMRF) model. A hybrid model integrating image spectral with abundance spatially dependent information is established to improve the accuracy of spectral mixture analysis. Simulated and real remote sensing images are used to validate the present method, and experiments show that this method can significantly improve abundance estimation, especially in noisy image.
\itemrv{~}
\itemcc{}
\itemut{remote sensing; spectral mixture analysis; Gaussian Markov random field model; abundance spatial dependence}
\itemli{}
\end