TY - GEN
T1 - Constrained-Target Band Selection Based on Band Combination for Hyperspectral Target Detection Using CEM
AU - Tian, Zhiyong
AU - Gao, Kun
AU - Zhang, Xiaodian
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - Selecting an appropriate band subset is a vital problem for hyperspectral target detection. The constrained-target band selection method, derived from constrained energy minimization (CEM), can select different band subsets according to different targets. The selected band will be used to detect the target by CEM. However, the current methods did not consider the adaptation of the selected band with CEM. We propose a constrained target band selection method based on band combination, which treats the selected band as a whole to match the input requirements of CEM to detect the specific target. Firstly, Criteria for evaluating band combination is proposed based on the constrained-target band selection method. Secondly, the features of these band combinations are proposed. Thirdly, the key band set is proposed to reduce the range of search band combinations from the whole band to a subset of the whole band, based on these features and the sparse constrained band selection (SCBS) method. Finally, the desired band combination is searched in the key band set based on these features. Experiments show that the proposed method offers promising results.
AB - Selecting an appropriate band subset is a vital problem for hyperspectral target detection. The constrained-target band selection method, derived from constrained energy minimization (CEM), can select different band subsets according to different targets. The selected band will be used to detect the target by CEM. However, the current methods did not consider the adaptation of the selected band with CEM. We propose a constrained target band selection method based on band combination, which treats the selected band as a whole to match the input requirements of CEM to detect the specific target. Firstly, Criteria for evaluating band combination is proposed based on the constrained-target band selection method. Secondly, the features of these band combinations are proposed. Thirdly, the key band set is proposed to reduce the range of search band combinations from the whole band to a subset of the whole band, based on these features and the sparse constrained band selection (SCBS) method. Finally, the desired band combination is searched in the key band set based on these features. Experiments show that the proposed method offers promising results.
KW - Band combination
KW - CEM
KW - Key band set
UR - http://www.scopus.com/inward/record.url?scp=85140408633&partnerID=8YFLogxK
U2 - 10.1109/IGARSS46834.2022.9883126
DO - 10.1109/IGARSS46834.2022.9883126
M3 - Conference contribution
AN - SCOPUS:85140408633
T3 - International Geoscience and Remote Sensing Symposium (IGARSS)
SP - 771
EP - 774
BT - IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2022 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2022
Y2 - 17 July 2022 through 22 July 2022
ER -