TY - GEN
T1 - Foreground Signature Extraction for an Intimate Mixing Model in Hyperspectral Image Classification
AU - Hollis, Jarrod
AU - Raich, Raviv
AU - Kim, Jinsub
AU - Fishbain, Barak
AU - Kendler, Shai
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/5
Y1 - 2020/5
N2 - The hyperspectral unmixing problem arises in remote sensing, chemometrics, and biomedical engineering applications. The spectral signature of a single pixel in a hyperspectral cube can be represented as a non-negative combination of non-negative signatures from various materials contained in the physical region corresponding to the pixel (linear mixing). A less studied problem is associated with foreground extraction in an intimate (nonlinear) mixing model. We introduce a framework for foreground signature extraction based on a proposed patch model. We introduce identifiability conditions for the single and multiple patch cases. Using these conditions, we present an algorithm for the identifiable recovery of foreground signatures. Numerical experiments on real and synthetic data illustrate the efficacy of the proposed approach.
AB - The hyperspectral unmixing problem arises in remote sensing, chemometrics, and biomedical engineering applications. The spectral signature of a single pixel in a hyperspectral cube can be represented as a non-negative combination of non-negative signatures from various materials contained in the physical region corresponding to the pixel (linear mixing). A less studied problem is associated with foreground extraction in an intimate (nonlinear) mixing model. We introduce a framework for foreground signature extraction based on a proposed patch model. We introduce identifiability conditions for the single and multiple patch cases. Using these conditions, we present an algorithm for the identifiable recovery of foreground signatures. Numerical experiments on real and synthetic data illustrate the efficacy of the proposed approach.
KW - endmember extraction
KW - hyperspectral imaging
KW - identifiability
KW - intimate mixing model
KW - nonnegative matrix factorization
UR - http://www.scopus.com/inward/record.url?scp=85089223497&partnerID=8YFLogxK
U2 - 10.1109/ICASSP40776.2020.9053456
DO - 10.1109/ICASSP40776.2020.9053456
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AN - SCOPUS:85089223497
T3 - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
SP - 4732
EP - 4736
BT - 2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020 - Proceedings
T2 - 2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020
Y2 - 4 May 2020 through 8 May 2020
ER -