• KIPS Transactions on Computer and Communication Systems
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• v.11 no.6
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• pp.185-192
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• 2022

Multimodal medical image fusion (MMIF) fuses two images containing different structural details generated in two different modes into a comprehensive image with saturated information, which can help doctors improve the accuracy of observation and treatment of patients' diseases. Therefore, a method based on double-layer decomposer and fine structure preservation model is proposed. Firstly, a double-layer decomposer is applied to decompose the source images into the energy layers and structure layers, which can preserve details well. Secondly, The structure layer is processed by combining the structure tensor operator (STO) and max-abs. As for the energy layers, a fine structure preservation model is proposed to guide the fusion, further improving the image quality. Finally, the fused image can be achieved by performing an addition operation between the two sub-fused images formed through the fusion rules. Experiments manifest that our method has excellent performance compared with several typical fusion methods.