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A Bayesian Approach to Linear Unmixing in the Presence of Highly Mixed Spectra
Abstract : In this article, we present a Bayesian algorithm for endmember extraction and abundance estimation in situations where prior information is available for the abundances. The algorithm is considered within the framework of the linear mixing model. The novelty of this work lies in the introduction of bound parameters which allow us to introduce prior information on the abundances. The estimation of these bound parameters is performed using a simulated annealing algorithm. The algorithm is illustrated by simulations conducted on synthetic AVIRIS spectra and on the SAMSON dataset.
Keywords :
linear mixing model
Source separation
https://hal.archives-ouvertes.fr/hal-01425738
Contributor : Michel Bilodeau Connect in order to contact the contributor
Submitted on : Tuesday, January 3, 2017 - 6:35:51 PM
Last modification on : Wednesday, November 17, 2021 - 12:27:13 PM
Contributor : Michel Bilodeau Connect in order to contact the contributor
Submitted on : Tuesday, January 3, 2017 - 6:35:51 PM
Last modification on : Wednesday, November 17, 2021 - 12:27:13 PM