TY - GEN
T1 - Spatiotemporal reflectance fusion based on location regularized sparse representation
AU - Liu, Xun
AU - Deng, Chenwei
AU - Zhao, Baojun
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/11/1
Y1 - 2016/11/1
N2 - Spatiotemporal reflectance fusion plays an important role in providing earth observation with both high-spatial and high-temporal resolutions, and sparse representation is one of the popular strategies to implement spatiotemporal fusion. However, the existing methods generally suffers from instability of sparse representation for the fine and coarse image pairs. In this paper, we demonstrate that such instability can be addressed by exploiting spatial correlations among the neighboring fine images, which is mathematically formulated as a location regularized term. A fast iterative shrinkage-thresholding algorithm (FISTA) is then employed to find the optimal solution. Experimental results show that the performance of proposed method outperforms other relevant state-of-the-art fusion approaches.
AB - Spatiotemporal reflectance fusion plays an important role in providing earth observation with both high-spatial and high-temporal resolutions, and sparse representation is one of the popular strategies to implement spatiotemporal fusion. However, the existing methods generally suffers from instability of sparse representation for the fine and coarse image pairs. In this paper, we demonstrate that such instability can be addressed by exploiting spatial correlations among the neighboring fine images, which is mathematically formulated as a location regularized term. A fast iterative shrinkage-thresholding algorithm (FISTA) is then employed to find the optimal solution. Experimental results show that the performance of proposed method outperforms other relevant state-of-the-art fusion approaches.
KW - fast iterative shrinkage-thresholding algorithm (FISTA)
KW - location regularized sparse representation
KW - spatiotemporal fusion
UR - http://www.scopus.com/inward/record.url?scp=85007433798&partnerID=8YFLogxK
U2 - 10.1109/IGARSS.2016.7729662
DO - 10.1109/IGARSS.2016.7729662
M3 - Conference contribution
AN - SCOPUS:85007433798
T3 - International Geoscience and Remote Sensing Symposium (IGARSS)
SP - 2562
EP - 2565
BT - 2016 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 36th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016
Y2 - 10 July 2016 through 15 July 2016
ER -