Multi-focus image fusion via gradient guidance progressive network.

In this paper, we address the problem of fusing multi-focus images in same scenes. We propose a gradient guidance progressive network for multi-focus image fusion. We explicitly extract gradient features of images, and introduce the gradient guidance progressive module to integrate effectively features. In the module, we employ low-resolution features with large receptive fields to detect focused areas far away from boundaries. While for high-resolution features incorporating detailed gradient features, we only focus on optimizing outputs near boundaries. Benefiting from the separate operations on both areas far away from and near boundaries, the proposed method makes accurate focus region detection with detailed boundaries. Experimental results demonstrate the effectiveness and superiority of the proposed method compared with the state-of-the-art methods.