Multi-Focus Image Fusion Method Based on Double-Scale Decomposition and Random Walk

This paper proposes a multi-focus image fusion method based on double-scale decomposition and random walk to smooth the edge region and avoid artifacts at the edge junction. The source images are first decomposed into large-scale and small-scale focus images using a Gaussian filter, and the edges of the decomposed large-scale and small-scale focus images are smoothed using various guiding filters. Then, the large-scale and small-scale focus maps are used as the marker nodes of the random walk algorithm, the initial decision map is obtained using the fusion algorithm, and the guided filter is used to optimize the decision map again. Finally, the source images are reconstructed using the decision graphs to produce the final fused image. The results of the experiments show that our method can effectively obtain the focus information in the source images while retaining the edge texture and detailed information of the focus area. It outperformed the competition in both subjective and objective evaluation indicators.