Image Fusion Algorithm Based on Wavelet Sparse Represented Compressed Sensing
Authors
Shan-shan Liu, Xiao-he Zhang, Ai Zheng
Corresponding Author
Shan-shan Liu
Available Online March 2013.
- DOI
- 10.2991/iccsee.2013.305How to use a DOI?
- Keywords
- compressed sensing, image fusion, wavelet, minimum total variation
- Abstract
On the basis of the compressed sensing theory, this study proposed an improved wavelet sparse represented compressed sensing based image fusion algorithm. This algorithm firstly got the wavelet sparse domain linear measurement values of the original images by the dual radial sampling mode. Then a simple maximum absolute value fusion rule was adopted on the compressed sensing domain. Finally, the minimum total variation method was used to reconstruct the fused image. The experiment result shows that this algorithm has good fusion effect.
- Copyright
- © 2013, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Shan-shan Liu AU - Xiao-he Zhang AU - Ai Zheng PY - 2013/03 DA - 2013/03 TI - Image Fusion Algorithm Based on Wavelet Sparse Represented Compressed Sensing BT - Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering (ICCSEE 2013) PB - Atlantis Press SP - 1214 EP - 1217 SN - 1951-6851 UR - https://doi.org/10.2991/iccsee.2013.305 DO - 10.2991/iccsee.2013.305 ID - Liu2013/03 ER -