Multifocus Image Fusion Based on Fast Guided Filter and Focus Pixels Detection

As an effective technique of information fusion, multifocus image fusion has attracted increasing attention for image processing and computer vision. The goal of multifocus image fusion method is integrating all focus information from source images into fused result. In this paper, we propose a novel simple and effective multifocus image fusion technique based on fast guided filter and focus pixels detection. In order to detect the focused pixels correctly from source images, we develop a new multi-scale sum modified Laplacian technique. For the decision maps learning stage, based on the block consistency verification and faster guided filter techniques, we generate a series of binary focus decision maps to express the focus property of each pixel. In the fusion stage, we employ neighbor distance filter to extract detail pixels of source images, then the informative highpass images and the energetic lowpass images can be generated. The fused results are developed by constructing the corresponding decision maps and the neighbor distance filtered images. Compared with some state-of-the-art fusion methods, experimental results clearly demonstrate the superiority of the proposed method in terms of both comprehensive subjective assessment and some well-known quantitative evaluations.