TY - GEN
T1 - Hyperspectral image super-resolution via adjacent spectral fusion strategy
AU - Li, Qiang
AU - Wang, Qi
AU - Li, Xuelong
N1 - Publisher Copyright:
© 2021 IEEE
PY - 2021
Y1 - 2021
N2 - Hyperspectral image exhibits low spatial resolution due to the limitation of imaging system. Improving it without an auxiliary high resolution (HR) image still remains a challenging problem. Recently, although many deep learning-based hyperspectral image super-resolution (SR) methods have been proposed, they make the insufficient utilization of adjacent bands to improve the reconstruction performance. To address this issue, we explore a new structure for hyperspectral image SR via adjacent spectral fusion strategy. Inspired by the high similarity among adjacent bands, neighboring band partition is proposed to divide the adjacent bands into several groups. Through the current band, the adjacent bands is guided to enhance the exploration ability. To explore more complementary information, an alternative fusion mechanism, i.e., intra-group fusion and inter-group fusion, is designed, which helps to recover the missing details in the current band. Experiments demonstrate that our approach produces the state-of-the-art results over the existing approaches.
AB - Hyperspectral image exhibits low spatial resolution due to the limitation of imaging system. Improving it without an auxiliary high resolution (HR) image still remains a challenging problem. Recently, although many deep learning-based hyperspectral image super-resolution (SR) methods have been proposed, they make the insufficient utilization of adjacent bands to improve the reconstruction performance. To address this issue, we explore a new structure for hyperspectral image SR via adjacent spectral fusion strategy. Inspired by the high similarity among adjacent bands, neighboring band partition is proposed to divide the adjacent bands into several groups. Through the current band, the adjacent bands is guided to enhance the exploration ability. To explore more complementary information, an alternative fusion mechanism, i.e., intra-group fusion and inter-group fusion, is designed, which helps to recover the missing details in the current band. Experiments demonstrate that our approach produces the state-of-the-art results over the existing approaches.
KW - Adjacent bands
KW - Group fusion
KW - Hyperspectral image
KW - Super-resolution (SR)
UR - http://www.scopus.com/inward/record.url?scp=85115176056&partnerID=8YFLogxK
U2 - 10.1109/ICASSP39728.2021.9413980
DO - 10.1109/ICASSP39728.2021.9413980
M3 - 会议稿件
AN - SCOPUS:85115176056
T3 - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
SP - 1645
EP - 1649
BT - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2021 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2021
Y2 - 6 June 2021 through 11 June 2021
ER -