10 April 2018 Multimodal medical image fusion by combining gradient minimization smoothing filter and non-subsampled directional filter bank
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Proceedings Volume 10615, Ninth International Conference on Graphic and Image Processing (ICGIP 2017); 1061532 (2018) https://doi.org/10.1117/12.2303626
Event: Ninth International Conference on Graphic and Image Processing, 2017, Qingdao, China
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.
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Cheng Zhang, Mei Wenbo, Du Huiqian, Wang Zexian, " Multimodal medical image fusion by combining gradient minimization smoothing filter and non-subsampled directional filter bank", Proc. SPIE 10615, Ninth International Conference on Graphic and Image Processing (ICGIP 2017), 1061532 (10 April 2018); doi: 10.1117/12.2303626; https://doi.org/10.1117/12.2303626
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