Proceedings of the 2017 5th International Conference on Mechatronics, Materials, Chemistry and Computer Engineering (ICMMCCE 2017)

<Previous Article In Volume
Next Article In Volume>

Block-based Compressive Sensing Image Fusion Method Based on Particle Swarm Optimization Algorithm

Authors
Xianhu Li, Jingguo Lv, Shan Jiang, Xin Pan
Corresponding Author
Xianhu Li
Available Online September 2017.
DOI
10.2991/icmmcce-17.2017.141How to use a DOI?
Keywords
Compressive sensing; Particle swarm optimization; Fusion coefficient; self-adaptability
Abstract

This In order to solve the problem that the spatial matching is difficult and the spectral distortion is large in traditional pixel-level image fusion algorithm. In this paper, we proposed an block-based compressive sensing image fusion method based on particle swarm optimization algorithm. We get the compressive measurements of input images by block-based compressive sensing (BCS) and fused them with the rule of linear weighting, while the fusion coefficients ( 1, 2, 3..., n , n is the divided number of blocks of the image to be fused) of each block were selected by particle swarm optimization algorithm. In the iterative process, the image fusion coefficient i is taken as particle, and the optimal value is obtained by combining the optimal objective function, taking the coefficient i as the weight value. The algorithm ensures the optimal selection of fusion effect with a certain degree of self-adaptability. To evaluate the fused images, this paper uses five kinds of index parameters such as Entropy, Standard Deviation, Average Gradient, Degree of Distortion and Peak Signal-to-Noise Ratio. The experimental results show that the image fusion effect of the algorithm in this paper is better than that of traditional methods.

Copyright
© 2017, 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/).

Download article (PDF)

<Previous Article In Volume
Next Article In Volume>
Volume Title
Proceedings of the 2017 5th International Conference on Mechatronics, Materials, Chemistry and Computer Engineering (ICMMCCE 2017)
Series
Advances in Engineering Research
Publication Date
September 2017
ISBN
10.2991/icmmcce-17.2017.141
ISSN
2352-5401
DOI
10.2991/icmmcce-17.2017.141How to use a DOI?
Copyright
© 2017, 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

risenwbib
TY  - CONF
AU  - Xianhu Li
AU  - Jingguo Lv
AU  - Shan Jiang
AU  - Xin Pan
PY  - 2017/09
DA  - 2017/09
TI  - Block-based Compressive Sensing Image Fusion Method Based on Particle Swarm Optimization Algorithm
BT  - Proceedings of the 2017 5th International Conference on Mechatronics, Materials, Chemistry and Computer Engineering (ICMMCCE 2017)
PB  - Atlantis Press
SP  - 783
EP  - 786
SN  - 2352-5401
UR  - https://doi.org/10.2991/icmmcce-17.2017.141
DO  - 10.2991/icmmcce-17.2017.141
ID  - Li2017/09
ER  -