TY - GEN
T1 - Estimating abundance fractions of materials in hyperspectral images by fitting a post-nonlinear mixing model
AU - Chen, Jie
AU - Richard, Cedric
AU - Honeine, Paul
N1 - Publisher Copyright:
© 2013 IEEE.
PY - 2013/6/28
Y1 - 2013/6/28
N2 - Within the area of hyperspectral data processing, nonlinear unmixing techniques have emerged as promising alternatives for overcoming the limitations of linear methods. In this paper, we consider the class of post-nonlinear mixing models of the partially linear form. More precisely, these composite models consist of a linear mixing part and a nonlinear fluctuation term defined in a reproducing kernel Hilbert space, both terms being parameterized by the endmember spectral signatures and their respective abundances. These models consider that the reproducing kernel may also depend advantageously on the fractional abundances. An iterative algorithm is then derived to jointly estimate the fractional abundances and to infer the nonlinear functional term.
AB - Within the area of hyperspectral data processing, nonlinear unmixing techniques have emerged as promising alternatives for overcoming the limitations of linear methods. In this paper, we consider the class of post-nonlinear mixing models of the partially linear form. More precisely, these composite models consist of a linear mixing part and a nonlinear fluctuation term defined in a reproducing kernel Hilbert space, both terms being parameterized by the endmember spectral signatures and their respective abundances. These models consider that the reproducing kernel may also depend advantageously on the fractional abundances. An iterative algorithm is then derived to jointly estimate the fractional abundances and to infer the nonlinear functional term.
KW - Hyperspectral data processing
KW - Kernel methods
KW - Nonlinear unmixing
KW - Post-nonlinear mixing model
UR - http://www.scopus.com/inward/record.url?scp=85038570643&partnerID=8YFLogxK
U2 - 10.1109/WHISPERS.2013.8080639
DO - 10.1109/WHISPERS.2013.8080639
M3 - 会议稿件
AN - SCOPUS:85038570643
T3 - Workshop on Hyperspectral Image and Signal Processing, Evolution in Remote Sensing
BT - 2013 5th Workshop on Hyperspectral Image and Signal Processing
PB - IEEE Computer Society
T2 - 5th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, WHISPERS 2013
Y2 - 26 June 2013 through 28 June 2013
ER -