Title :
Remote sensing image fusion through kernel estimation based on energy minimization
Author :
Xie, Q.W. ; Liu, Zhe ; Qian, Liejia ; Mita, Seiichi ; Jiang, Aimin
Author_Institution :
Res. Center for Smart Vehicles, Toyota Technol. Inst., Nagoya, Japan
Abstract :
This paper reports the improvement of image quality issue in the fusion of remote sensing images by minimizing an energy function. By gradient constraint term of the energy function, the spatial information of the panchromatic image was transferred to fused results. The spectral information of multispectral image was preserved by importing a kernel function to the data fitting term of the energy function. Visual perception measurement and selected fusion metrics were employed to evaluate the fusion performance. Experimental results demonstrated the proposed method outperforms other established image fusion techniques.
Keywords :
image fusion; remote sensing; traffic engineering computing; data fitting term; energy function; energy minimization; fusion metrics; gradient constraint term; image quality issue; kernel estimation; kernel function; multispectral image; panchromatic image; remote sensing image fusion; spectral information; visual perception measurement; Equations; Image fusion; Image resolution; Kernel; Mathematical model; Measurement; Remote sensing;
Conference_Titel :
Intelligent Transportation Systems (ITSC), 2014 IEEE 17th International Conference on
Conference_Location :
Qingdao
DOI :
10.1109/ITSC.2014.6957702