3M: A Multi-Scale and Multi-Directional Method for Multi-Focus Image Fusion

Based on the analysis of the multi-scale-based and sparse representation-based multi-focus image fusion method, we believe that a multi-scale fusion method should consider the directivity of high/low frequency sub-bands and low computational complexity, ensuring the effectiveness and efficiency. Therefore, we propose a novel multi-focus image fusion algorithm based on multi-scale and multi-directional dictionaries. In the proposed method, source images are decomposed by multi-scale transform(MST) to obtain high/low frequency sub-bands. For the high-frequency part, a direction contrast-based fusion rule is presented. For the low-frequency part, the image patches are divided into strong/weak information patches. The strong information patches are merged with a fusion approach based on directional dictionaries, while the weak information patches are fused using weighted average. Finally, the fused image is obtained by performing the inverse MST. The experimental results show that the proposed approach extracts more important effective information from source images, and the computational efficiency is greatly improved.