A Multilinear Mixing Model for Nonlinear Spectral Unmixing

被引:142
|
作者
Heylen, Rob [1 ]
Scheunders, Paul [2 ]
机构
[1] Univ Antwerp, Dept Phys, iMinds Vis Lab, B-2610 Antwerp, Belgium
[2] Univ Antwerp, Dept Phys, Vis Lab, B-2610 Antwerp, Belgium
来源
关键词
Hyperspectral imaging; spectral analysis; BIDIRECTIONAL REFLECTANCE; HYPERSPECTRAL IMAGES; MIXTURE ANALYSIS; CLASSIFICATION; VEGETATION;
D O I
10.1109/TGRS.2015.2453915
中图分类号
P3 [地球物理学]; P59 [地球化学];
学科分类号
0708 ; 070902 ;
摘要
In hyperspectral unmixing, bilinear and linear-quadratic models have become popular recently, and also the polynomial postnonlinear model shows promising results. These models do not consider endmember interactions involving more than two endmembers, although such interactions might compose a nontrivial part of the observed spectrum in scenarios involving bright materials and complex geometrical structures, such as vegetation and intimate mixtures. In this paper, we present an extension of these models to include an infinite number of interactions. Several technical problems, such as divergence of the resulting series, can be avoided by introducing an optical interaction probability, which becomes the only free parameter of the model in addition to the abundances. We present an unmixing strategy based on this multilinear mixing (MLM) model; present comparisons with the bilinear models and the Hapke model for intimate mixing; and show that, in several scenarios, the MLM model obtains superior results.
引用
收藏
页码:240 / 251
页数:12
相关论文
共 50 条
  • [1] Unsupervised Nonlinear Spectral Unmixing Based on a Multilinear Mixing Model
    Wei, Qi
    Chen, Marcus
    Tourneret, Jean-Yves
    Godsill, Simon
    [J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2017, 55 (08): : 4534 - 4544
  • [2] NONLINEAR UNMIXING WITH A MULTILINEAR MIXING MODEL
    Heylen, Rob
    Scheunders, Paul
    [J]. 2015 7TH WORKSHOP ON HYPERSPECTRAL IMAGE AND SIGNAL PROCESSING: EVOLUTION IN REMOTE SENSING (WHISPERS), 2015,
  • [3] A Graph Regularized Multilinear Mixing Model for Nonlinear Hyperspectral Unmixing
    Li, Minglei
    Zhu, Fei
    Guo, Alan J. X.
    Chen, Jie
    [J]. REMOTE SENSING, 2019, 11 (19)
  • [4] Spectral-Spatial Reweighted Robust Nonlinear Unmixing for Hyperspectral Images Based on an Extended Multilinear Mixing Model
    Li, Minglei
    Yang, Bin
    Wang, Bin
    [J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2022, 60
  • [5] ROBUST NONLINEAR UNMIXING FOR HYPERSPECTRAL IMAGES BASED ON AN EXTENDED MULTILINEAR MIXING MODEL
    Li, Minglei
    Yang, Bin
    Wang, Bin
    [J]. 2022 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS 2022), 2022, : 1780 - 1783
  • [6] Band-Wise Nonlinear Unmixing for Hyperspectral Imagery Using an Extended Multilinear Mixing Model
    Yang, Bin
    Wang, Bin
    [J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2018, 56 (11): : 6747 - 6762
  • [7] SPECTRAL VARIABILITY IN A MULTILINEAR MIXING MODEL
    Dox, Thorvald
    Heylen, Rob
    Scheunders, Paul
    [J]. IGARSS 2018 - 2018 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, 2018, : 4217 - 4220
  • [8] Supervised Nonlinear Spectral Unmixing Using a Postnonlinear Mixing Model for Hyperspectral Imagery
    Altmann, Yoann
    Halimi, Abderrahim
    Dobigeon, Nicolas
    Tourneret, Jean-Yves
    [J]. IEEE TRANSACTIONS ON IMAGE PROCESSING, 2012, 21 (06) : 3017 - 3025
  • [9] A Coarse-to-Fine Scheme for Unsupervised Nonlinear Hyperspectral Unmixing Based on an Extended Multilinear Mixing Model
    Li, Minglei
    Yang, Bin
    Wang, Bin
    [J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2023, 61
  • [10] Bilinear normal mixing model for spectral unmixing
    Luo, Wenfei
    Gao, Lianru
    Zhang, Ruihao
    Marinoni, Andrea
    Zhang, Bing
    [J]. IET IMAGE PROCESSING, 2019, 13 (02) : 344 - 354