Multisensor Video Fusion Based on Surfacelet Transform

Qiang Zhang; Hui Juan Li; Zhao Kun Ma

doi:10.4028/www.scientific.net/AMR.341-342.163

Paper Titles

Powder Mixed Micro Electro Discharge Milling of Titanium Alloy: Analysis of Surface Roughness
p.142

Investigation of Grinding Surface Temperature: Experimental Measurements and Numerical Modeling
p.147

Optimization and Implementation of the Surface Rendering Algorithm
p.152

Automatic Classification of Dayside Aurora in All-Sky Images Using a Multi-Level Texture Feature Representation
p.158

Multisensor Video Fusion Based on Surfacelet Transform
p.163

Fast Content Based Color Image Retrieval System Based on Texture Analysis of Edge Map
p.168

The Carbon Fiber Composite Materials Application in Sports Equipment
p.173

Numerical Simulation on Thixocasting Process of Auto Box-Like
p.177

Light-Weighting Design of Eco-Power Automobile Chassis Made from Green Composite and its Topology Optimization in FEA
p.183

HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 341-342Multisensor Video Fusion Based on Surfacelet...

Multisensor Video Fusion Based on Surfacelet Transform

Abstract:

Based on the three dimensional surfacelet transform, a novel multisensor video fusion algorithm is proposed, in which, multiple frames of input videos are regarded as special three dimensional signals and fused as a whole rather than frame by frame. Meanwhile, selection principles for different subband coefficients are discussed in detail. Experimental results demonstrate that the proposed algorithm outperforms the traditional individual-frame-based and motion-based methods in spatial-temporal information extraction as well as in temporal stability and consistency. In addition, it does not require the motion target detection pre-step and is easy to implement.

You might also be interested in these eBooks

Material and Manufacturing Technology II

View Preview

Info:

Periodical:

Advanced Materials Research (Volumes 341-342)

Pages:

163-167

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.341-342.163

Citation:

Cite this paper

Online since:

September 2011

Authors:

Qiang Zhang, Hui Juan Li, Zhao Kun Ma

Keywords:

Spatial-Temporal Information, Surfacelet Transform, Video Fusion

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] K. Amonlis, Y. Zhang and P. Dare: ISPRS Journal of Photogrammetry & Remote Sensing, Vol. 62(2007), p.249.

Google Scholar

[2] S. Denman, T. Lamb, C. Fookes, V. Chandran, and S. Sridharan: Computers and Electrical Engineering, Vol. 36(2010), p.643.

DOI: 10.1016/j.compeleceng.2008.11.011

Google Scholar

[3] O. Rockinger: IEEE Transactions on Image Processing, Vol. 3(1997), p, 288.

Google Scholar

[4] C.Y. Liu, Z.L. Jing, G. Xiao and B. Yang: Chinese Optics Letters, 5, 274(2007).

Google Scholar

[5] J. Li, S.G. Nikolov, C.P. Benton and N.E. Scott-Samuel, in: 9th International Conference on Information Fusion, Publication Date: 10-13 July, 2006, pp.1-8.

Google Scholar

[6] Y.M. Lu, M.N. Do: IEEE Transactions on Image Processing, Vol. 16(2007), p.918.

Google Scholar

[7] M.N. Do, M. Vetterli: IEEE Transactions on Image Processing, Vol. 14 (2005), p. (2091).

Google Scholar

[8] Z. Zhang, R.S. Blum: Proceedings of the IEEE, Vol. 87 (1999), p.1315.

Google Scholar

[9] Q. Zhang, B.L. Guo: Signal Processing, Vol. 87 (2009), p.1334.

Google Scholar

[10] V. Xydeas, V. Petrovic: Electronics Letters, Vol. 36 (2000), p.308.

Google Scholar

[11] V. Petrovic, T. Cootes, R. Pavlovic, in: 10th IEEE International Conference on Information Fusion, 2007, pp.1-7.

Google Scholar