Multifocus image fusion with enhanced linear spectral clustering and fast depth map estimation

One novel regional method is proposed in this paper to get more natural multifocus image fusion results. At first, the edge defocus degree propagation approach is combined with the linear-time guided filter to generate the depth information of all pixels efficiently. Then the fast linear spectral clustering (LSC) is enhanced by the depth information to produce superpixels as regions. Due to the embedding of depth information in the clustering algorithm, the resulting regions are more consistent with the distributions of pixels in source images with different focus levels. The flexibility in selecting the number of superpixels also offers the enhanced LSC a better chance to get more homogeneous segmentation, which is of great importance in deriving better fusion results. Finally a post-processing step based on multi-guided filtering and morphological operations is suggested to polish the decision map of fusion and further improve the fusion results. Experiments demonstrate that the proposed method can achieve state-of-the-art performance for multifocus image fusion problems.