Multi-focus Image Fusion Based on Multiple CNNs in NSCT Domain

In order to overcome the boundary information loss in the image fusion with single convolutional neural network, this paper proposes a novel multi-focus image fusion with multiple convolutional neural networks in nonsubsampled contourlet transform (NSCT) domain. First, the source images are decomposed into a low frequency sub-band and a serious of high frequency sub-bands by using NSCT. Second, a corresponding CNN model for each level of high frequency sub-bands is trained to fuse them. Then, an averaging rule is employed to fuse the low frequency sub-bands. Finally, the fused image is reconstructed by performing inverse NSCT on the fused sub-bands. Experimental results illustrate that the proposed method is superior to several existing multi-focus image fusion methods in terms of both executive evaluation and objective evaluation.