A simple and effective multi-focus image fusion method based on local standard deviations enhanced by the guided filter

This paper develops a simple and effective multi-focus image fusion method based on local standard deviations of the corresponding Laplacian images of source images and further enhanced by the guided filter. The underlying idea of this pixel-based approach is that the sharper pixels generally should have a comparatively higher local variance and hence higher local standard deviation. We first apply the Laplacian operation on each partially focused source image of the same scene, estimate the local standard deviation for each pixel, and enhance the local standard deviations using the guided filter. We then employ the filtered local standard deviation of the Laplacian image as an initial focus measure and combine it with the small region removal strategy to construct a decision map for pixel selection. Finally, according to the decision map, the target all in-focus fused image is formed pixel-by-pixel. A variant of the proposed method with further guided filtering on the decision map is also developed. Numerical results demonstrate the proposed methods' high performance compared with some state-of-the-art techniques.

Automated summary

This paper presents a pixel-based method for multi-focus image fusion, which selects sharper pixels based on local standard deviations and further enhances the fusion quality using a guided filter. Experimental results demonstrate that the proposed method outperforms other state-of-the-art techniques in terms of performance.