TY - GEN
T1 - Spatially regularzied sparsecem for target detection in hyperspectral images
AU - Yang, Xiaoli
AU - Li, Zeng
AU - Chen, Jie
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/10/31
Y1 - 2018/10/31
N2 - Constrained energy minimization (CEM) is a popular method for target detection in hyperspectral images. Its variant SparseCEM uses a sparsity regularization term to promote the sparsity of the detection output. However, these approaches do not consider the spatial correlation of hyperspectral pixels, and target detection can further benefit from exploiting the spatial information. In this paper, we propose a novel constrained detection algorithm, referred to as Spatial-SparseCEM, to simultaneously force the sparsity of the output and piecewise continuity via proper regularizations. The formulated problem is solved efficiently by using alternating direction method of multipliers (ADMM). We illustrate the enhanced performance of the Spatial-SparseCEM algorithm via both synthetic and real hyperspectral data.
AB - Constrained energy minimization (CEM) is a popular method for target detection in hyperspectral images. Its variant SparseCEM uses a sparsity regularization term to promote the sparsity of the detection output. However, these approaches do not consider the spatial correlation of hyperspectral pixels, and target detection can further benefit from exploiting the spatial information. In this paper, we propose a novel constrained detection algorithm, referred to as Spatial-SparseCEM, to simultaneously force the sparsity of the output and piecewise continuity via proper regularizations. The formulated problem is solved efficiently by using alternating direction method of multipliers (ADMM). We illustrate the enhanced performance of the Spatial-SparseCEM algorithm via both synthetic and real hyperspectral data.
KW - ADMM
KW - Constrained energy minimization
KW - Hyperspectral image
KW - Spatially-regularized detection
KW - Target detection
KW - ℓ1-norm regularization
UR - http://www.scopus.com/inward/record.url?scp=85064170899&partnerID=8YFLogxK
U2 - 10.1109/IGARSS.2018.8518691
DO - 10.1109/IGARSS.2018.8518691
M3 - 会议稿件
AN - SCOPUS:85064170899
T3 - International Geoscience and Remote Sensing Symposium (IGARSS)
SP - 2765
EP - 2768
BT - 2018 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 38th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018
Y2 - 22 July 2018 through 27 July 2018
ER -