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Proceedings Paper

Fusion of noisy images based statistical model in shearlet domain
Author(s): Chengzhi Deng; Xin Hu
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Paper Abstract

A new image fusion approach based on the modeling of shearlet coefficients with normal inverse gaussian model is proposed. The approach focus on the fusion of noisy images. Based on the statistical model and additive white gaussian noise, an subband adaptive shrinkage function is derived by using the maximum a posteriori rule. And then, the new scheme for shearlet-domain image fusion is proposed by incorporating the adaptive shrinkage rule into the fusion scheme. Experimental results show the proposed method perfor very well with noisy images, outperform other conventional methods.

Paper Details

Date Published: 23 November 2011
PDF: 6 pages
Proc. SPIE 8006, MIPPR 2011: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications, 80060Y (23 November 2011); doi: 10.1117/12.901982
Show Author Affiliations
Chengzhi Deng, Nanchang Institute of Technology (China)
Xin Hu, Jiangxi Science and Technology Normal Univ. (China)


Published in SPIE Proceedings Vol. 8006:
MIPPR 2011: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications
Faxiong Zhang; Faxiong Zhang, Editor(s)

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