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| Hierarchical Optimization for MultiFundus Image Fusion |
1 College of Computer and Information Fujian Agriculture and Forestry University，Fuzhou 350002, China
2 College of Physics and Information Engineering Fuzhou University，Fuzhou 350002, China |
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Abstract In order to remove the seams and ensure information details are not missed in the image fusion, the multiband blending image fusion method for multifundus image was proposed in this paper based on hierarchical optimization fusion. The mask image is achieved by multithreshold segmentation
and Euclidean distance transform. And the improved weighted coefficients are designed based on the distance value in the overlap region and the layers of Gaussian image sum of Laplacian energy for the mask image. The combined objective evaluation was proposed that it is based on information entropy, spatial frequency and definition. The registration error and overlap rate are used to realize hierarchical optimization multiband image fusion method for grouping fusion. And the image alone is put into next level directly. 75 group image sequences are applied involving 4 898 set of images (normal fundus image 2 952 pairs and disease fundus image 1 946 pairs) for testing and validation. The results show that the proposed method is effective that removes the seam and obtains the RMSE value of about (01±005) pixels in overlap region. The proposed method can make equilibrium between objective evaluation and subjective visual effect.
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