Multi-Focus Image Fusion Through Gradient-Based Decision Map Construction and Mathematical Morphology

Multi-focus image fusion is an important technique that extracts sharp regions from multiple images and composites them into a fully focused image. In this paper, a novel spatial domain-based fusion algorithm for multi-focus images through gradient-based decision map construction and mathematical morphology is proposed. The contributions of this paper are: 1) a weighted kernel based on image gradient is proposed to measure focus regions; 2) the boundaries between focus and defocus regions are adjusted by morphological operations and free boundary condition-based active contour model. Though the weighted kernel, the focus regions are roughly identified. Moreover, after the morphological operations and the adjustment of boundaries using active contour model, the true boundaries between the focused and defocused regions are extracted. The experimental results demonstrate that the proposed algorithm performs better than the other eight representative fusion algorithms in both the qualitative and quantitative evaluations.