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Optical Engineering

Adaptive remote sensing image fusion under the framework of data assimilation
Author(s): Rongyuan Chen; Wei Xie; Leiguang Wang; Qianqing Qin
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Paper Abstract

The existing fusion methods cannot adjust fused images, adaptively according to the requirements of follow-up image processing steps, as well as the merits of different fusion methods, and are not easy to be integrated. Since a data assimilation system can integrate the advantage of a model operator and observer operator, a fusion framework based on the data assimilation concept is proposed, which can adaptively fuse different remote sensing images. Under this framework, a fusion method based on an independent component analysis and àtrous wavelet transform is used as a model operator, and another fusion method based on nonsubsampled contourlet transform is used as an observation operator. Meanwhile, image quantitative evaluation indicators are used as an objective function. Then, the genetic particle swarm algorithm is employed to optimize the objective function in order to gain a more suitable image. Finally, three sets of panchromatic images and multispectral images are used in experiments. The results show that the proposed algorithm can adjust fusion results adaptively, according to a particular objective function.

Paper Details

Date Published: 1 June 2011
PDF: 11 pages
Opt. Eng. 50(6) 067006 doi: 10.1117/1.3584839
Published in: Optical Engineering Volume 50, Issue 6
Show Author Affiliations
Rongyuan Chen, Hunan Univ. of Commerce (China)
Wei Xie, Wuhan Univ. (China)
Leiguang Wang, Wuhan Univ. (China)
Qianqing Qin, Wuhan Univ. (China)

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