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Multimodal medical image fusion by combining gradient minimization smoothing filter and non-subsampled directional filter bank
Author(s): Cheng Zhang; Mei Wenbo; Du Huiqian; Wang Zexian
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Paper Abstract

A new algorithm was proposed for medical images fusion in this paper, which combined gradient minimization smoothing filter (GMSF) with non-sampled directional filter bank (NSDFB). In order to preserve more detail information, a multi scale edge preserving decomposition framework (MEDF) was used to decompose an image into a base image and a series of detail images. For the fusion of base images, the local Gaussian membership function is applied to construct the fusion weighted factor. For the fusion of detail images, NSDFB was applied to decompose each detail image into multiple directional sub-images that are fused by pulse coupled neural network (PCNN) respectively. The experimental results demonstrate that the proposed algorithm is superior to the compared algorithms in both visual effect and objective assessment.

Paper Details

Date Published: 10 April 2018
PDF: 5 pages
Proc. SPIE 10615, Ninth International Conference on Graphic and Image Processing (ICGIP 2017), 1061532 (10 April 2018); doi: 10.1117/12.2303626
Show Author Affiliations
Cheng Zhang, Beijing Institute of Technology (China)
Mei Wenbo, Beijing Institute of Technology (China)
Du Huiqian, Beijing Institute of Technology (China)
Wang Zexian, Beijing Institute of Technology (China)


Published in SPIE Proceedings Vol. 10615:
Ninth International Conference on Graphic and Image Processing (ICGIP 2017)
Hui Yu; Junyu Dong, Editor(s)

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