Multimodal medical image fusion based on guided filtered multi-scale decomposition Online publication date: Tue, 17-May-2016
by Pritika; Sumit Budhiraja
International Journal of Biomedical Engineering and Technology (IJBET), Vol. 20, No. 4, 2016
Abstract: Multimodal image fusion plays a pivotal role in medical field by fusing the complementary information of different modalities like CT and MRI into a single image. Widely used transform domain and recently proposed guided filter-based spatial domain image fusion techniques are limited by contrast reduction and halo artefacts. In this paper, an image fusion scheme based on the guided filtered multi-scale decomposition is proposed. First, the source images are decomposed into a base layer and series of detail layers by using guided filter. Then, different fusion rules are employed for fusing the base layer and detail layers. Simulation results show that the proposed fusion technique performs better than the traditional techniques in preserving salient features in the fused image without producing distortion.
Online publication date: Tue, 17-May-2016
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