Image fusion with guided saliency

Abstract

To obtain maximum possible details from source imagery, we propose a fast and effective image fusion method with guided saliency(IFGS). Our method first computes the saliency maps of all source images, and then each guided saliency map is generated using Logarithmic spectrum with an adaptive threshold value. Next, the weight of each component is computed by the guided gradient (FGG) method. Finally, the coefficients of the fused image are obtained by linearly combining the weights of the source images with the coefficients of the corresponding images. Experimental results demonstrate that our method can generate high-quality fusion images with better color and more details from multi-focus and multi-exposure compared to other fusion methods.