TY - GEN
T1 - Joint low rank and sparse representation-based hyperspectral image classification
AU - Zhang, Mengmeng
AU - Li, Wei
AU - Du, Qian
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/6/28
Y1 - 2016/6/28
N2 - Representation-based classification has gained great interest recently. In this paper, we present a novel joint low rank and sparse representation-based classification (JLRSRC) method for hyperspectral imagery. For a testing set, JLRSRC seeks weight coefficients to represent a testing pixel as linear combination of atoms in an over-complete dictionary. Since the low rank model is capable of preserving global data structures of data while sparsity can select the discriminative neighbors in the feature space, the resulting representation is both representative and discriminative. Experimental results demonstrate the effectiveness of the proposed JLRSRC when compared with the traditional counterparts.
AB - Representation-based classification has gained great interest recently. In this paper, we present a novel joint low rank and sparse representation-based classification (JLRSRC) method for hyperspectral imagery. For a testing set, JLRSRC seeks weight coefficients to represent a testing pixel as linear combination of atoms in an over-complete dictionary. Since the low rank model is capable of preserving global data structures of data while sparsity can select the discriminative neighbors in the feature space, the resulting representation is both representative and discriminative. Experimental results demonstrate the effectiveness of the proposed JLRSRC when compared with the traditional counterparts.
KW - Hyperspectral imagery
KW - Low rank representation
KW - Pattern classification
KW - Sparse representation
UR - https://www.scopus.com/pages/publications/85037543233
U2 - 10.1109/WHISPERS.2016.8071748
DO - 10.1109/WHISPERS.2016.8071748
M3 - Conference contribution
AN - SCOPUS:85037543233
T3 - Workshop on Hyperspectral Image and Signal Processing, Evolution in Remote Sensing
BT - 2016 8th Workshop on Hyperspectral Image and Signal Processing
PB - IEEE Computer Society
T2 - 8th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, WHISPERS 2016
Y2 - 21 August 2016 through 24 August 2016
ER -