TY - GEN
T1 - Hyperspectral and Multispectral Image Fusion Using Non-Convex Relaxation Low Rank and Total Variation Regularization
AU - Yuan, Yue
AU - Wang, Qi
AU - Li, Xuelong
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/9/26
Y1 - 2020/9/26
N2 - Hyperspectral (HS) and multispectral (MS) image fusion is an important task to construct an HS image with high spatial and spectral resolutions. In this paper, we present a novel HS and MS fusion method using non-convex low rank tensor approximation and total variation regularization. In specific, the Laplace based low-rank model is formed to exploit spatial-spectral correlation and nonlocal similarity of the HS image, and the second-order total variation is used to describe the local smoothness structure in the spatial domain and adjacent bands. Also, an effective optimization algorithm is designed for the proposed model. In the experiments, we demonstrate the superiority of the proposed method compared to several state-of-the-art approaches.
AB - Hyperspectral (HS) and multispectral (MS) image fusion is an important task to construct an HS image with high spatial and spectral resolutions. In this paper, we present a novel HS and MS fusion method using non-convex low rank tensor approximation and total variation regularization. In specific, the Laplace based low-rank model is formed to exploit spatial-spectral correlation and nonlocal similarity of the HS image, and the second-order total variation is used to describe the local smoothness structure in the spatial domain and adjacent bands. Also, an effective optimization algorithm is designed for the proposed model. In the experiments, we demonstrate the superiority of the proposed method compared to several state-of-the-art approaches.
KW - Hyperspectral (HS) image
KW - image fusion
KW - low-rank approximation
KW - multispectral (MS) image
KW - total variation
UR - http://www.scopus.com/inward/record.url?scp=85089412816&partnerID=8YFLogxK
U2 - 10.1109/IGARSS39084.2020.9323227
DO - 10.1109/IGARSS39084.2020.9323227
M3 - 会议稿件
AN - SCOPUS:85089412816
T3 - International Geoscience and Remote Sensing Symposium (IGARSS)
SP - 2683
EP - 2686
BT - 2020 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2020 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2020 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2020
Y2 - 26 September 2020 through 2 October 2020
ER -