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Proceedings Paper

Algorithm for image fusion via gradient correlation and difference statistics
Author(s): Jing Han; Li-juan Wang; Yi Zhang; Lian-fa Bai; Ningjie Mao
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Paper Abstract

In order to overcome the shortcoming of traditional image fusion based on discrete wavelet transform (DWT), a novel image fusion algorithm based on gradient correlation and difference statistics is proposed in this paper. The source images are decomposed into low-frequency coefficients and high-frequency coefficients by DWT: the former are fused by a local gradient correlation based scheme to extract the local feature information in source images; the latter are fused by a neighbor difference statistics based scheme to reserve the conspicuous edge information. Finally, the fused image is reconstructed by inverse DWT. Experimental results show that the proposed method performs better than other methods in reserving details.

Paper Details

Date Published: 25 October 2016
PDF: 12 pages
Proc. SPIE 10157, Infrared Technology and Applications, and Robot Sensing and Advanced Control, 101571N (25 October 2016); doi: 10.1117/12.2246618
Show Author Affiliations
Jing Han, Nanjing Univ. of Science and Technology (China)
Li-juan Wang, Nanjing Univ. of Science and Technology (China)
Yi Zhang, Nanjing Univ. of Science and Technology (China)
Lian-fa Bai, Nanjing Univ. of Science and Technology (China)
Ningjie Mao, China Electronics Technology Group Corp. (China)


Published in SPIE Proceedings Vol. 10157:
Infrared Technology and Applications, and Robot Sensing and Advanced Control

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