Regular Articles

Image fusion method based on the advection equation

[+] Author Affiliations
Kai Liu

Southeast University, School of Computer Science and Engineering, Jiangsu, Sipailou Campus, Nanjing 210096, China

PLA University of Science and Technology, Institute of Meteorology and Oceanography, Jiangsu, No. 60 Shuanglong Street, Nanjing 211101, China

Limin Luo

Southeast University, School of Computer Science and Engineering, Jiangsu, Sipailou Campus, Nanjing 210096, China

Zheng Kou

PLA University of Science and Technology, Institute of Meteorology and Oceanography, Jiangsu, No. 60 Shuanglong Street, Nanjing 211101, China

PLA University of Science and Technology, National Key Laboratory on Electromagnetic Environmental Effects and Electro-optical Engineering, China, No. 60 Shuanglong Street, Nanjing 211101, China

J. Electron. Imaging. 23(1), 013019 (Feb 06, 2014). doi:10.1117/1.JEI.23.1.013019
History: Received April 26, 2013; Revised December 22, 2013; Accepted January 3, 2014
Text Size: A A A

Abstract.  We present an innovative method based on the linear advection equation, an important partial differential equation, to perform the fusion of images. The basic idea of this method is to insert the relevant information from other source images into the current source image through an advection process. Furthermore, we present the discrete scheme of this model and compare it with classical fusion approaches, the diffusion equation-based method, and some state-of-the-art fusion approaches on three groups of fusion images that are often used in the image fusion research. The results of experiments show that the fusion method based on the advection equation is comparable with the best of the classical, diffusion-based, and state-of-the-art methods. The high “weighted performance metric” QAB/F of fused images certifies that the relevant information is well injected from the input to the output images. Moreover, this method has fewer adjustable parameters with settings that affect the metric QAB/F less than other methods, and the evolution from input to output is also faster than the diffusion-based method. In addition, this model allows us to cope with noisy source image fusion by adding a diffusion term in the equation, thereby combining the denoising process with the fusion process.

Figures in this Article
© 2014 SPIE and IS&T

Citation

Kai Liu ; Limin Luo and Zheng Kou
"Image fusion method based on the advection equation", J. Electron. Imaging. 23(1), 013019 (Feb 06, 2014). ; http://dx.doi.org/10.1117/1.JEI.23.1.013019


Access This Article
Sign in or Create a personal account to Buy this article ($20 for members, $25 for non-members).

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging & repositioning the boxes below.

Related Book Chapters

Topic Collections

PubMed Articles
Advertisement
  • Don't have an account?
  • Subscribe to the SPIE Digital Library
  • Create a FREE account to sign up for Digital Library content alerts and gain access to institutional subscriptions remotely.
Access This Article
Sign in or Create a personal account to Buy this article ($20 for members, $25 for non-members).
Access This Proceeding
Sign in or Create a personal account to Buy this article ($15 for members, $18 for non-members).
Access This Chapter

Access to SPIE eBooks is limited to subscribing institutions and is not available as part of a personal subscription. Print or electronic versions of individual SPIE books may be purchased via SPIE.org.