Proceedings of the 2nd International Conference on Mechatronics Engineering and Information Technology (ICMEIT 2017)

Remote sensing image multi-feature fusion based on NSCT transform and compressive sensing

Authors
Zhiliang Wu, Yongdong Huang, Kang Zhang
Corresponding Author
Zhiliang Wu
Available Online May 2017.
DOI
https://doi.org/10.2991/icmeit-17.2017.22How to use a DOI?
Keywords
Remote sensing image fusion, NSCT transform, compressive sensing, multi-feature fusion.
Abstract
For the remote sensing image fusion algorithm based on non-subsampled Contourlet transform (NSCT) calculation complexity and cannot extract details from source images effectively. So a new remote sensing image multi-feature fusion algorithm based on NSCT transform and compressive sensing is proposed. Firstly, luminance component V of multi-spectral image is extracted via HSV transform, and decompose the luminance component V and PAN image by NSCT; Then, Apply PCNN-based fusion rules to fusing low frequency sub-band, and the equivalent number is utilized as the linking strength; For the high frequency sub-band, a fusion rule based on the multi-feature in compressive sensing domain is presented; Finally, the fused images are obtained by inverse NSCT transform and inverse HSV transform, respectively. The experimental results show that the proposed fusion algorithm substantially outperforms the best-known remote sensing image fusion algorithms in terms of calculation complexity and the quality of the fused image, and has the better performance in visual effect and objective evaluation metrics
Open Access
This is an open access article distributed under the CC BY-NC license.

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Cite this article

TY  - CONF
AU  - Zhiliang Wu
AU  - Yongdong Huang
AU  - Kang Zhang
PY  - 2017/05
DA  - 2017/05
TI  - Remote sensing image multi-feature fusion based on NSCT transform and compressive sensing
BT  - Proceedings of the 2nd International Conference on Mechatronics Engineering and Information Technology (ICMEIT 2017)
PB  - Atlantis Press
SP  - 115
EP  - 119
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmeit-17.2017.22
DO  - https://doi.org/10.2991/icmeit-17.2017.22
ID  - Wu2017/05
ER  -