A Medical Image Fusion Algorithm Based on Nonsubsampled Contourlet Transform and Feature Matching
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Jionghui Jiang, Hui Huang, Gang Liu
By analysis the regional characteristics of Low-frequency subbands and high-frequency subbands in nonsubsampled Contourlet transform (NSCT) for medical images, we proposed an NSCT-based image fusion algorithm for medical images. For each coefficient of the low-frequency subbands, the regional correlation was considered and the fusion strategy based on regional clarity matching was used; for each coefficient of the high-frequency subbands, the directional characteristics of the subbands were considered and the fusion strategy based on local energy of high-frequency regions was used; after that, the high-frequency fusion coefficient was determined. The proposed algorithm was verified through a simulation experiment on CT, PET and MRI images. The fusion effect was assessed using subjective and objective evaluation indicators. The experiment showed that the proposed algorithm achieved a better visual quality and quantitative indicators for medical images.
Image Fusion, NSCT, Directional characteristic.