A new focus evaluation operator based on max-min filter and its application in high quality multi-focus image fusion

Multi-focus image fusion plays an important role in the field of image recognition and analysis. However, current focus evaluation operators are complex and inefficiency. In this paper, a new focus evaluation operator based on max-min filter is proposed. In new focus measure, we use max-min filter with the help of average filter and median filter (MMAM) to evaluate the focus degree of source images. This evaluation algorithm can well measure the sharpness of different regions of the image, and the selected clear region will be more useful for human visual or machine perception. The experiment proved that MMAM can perform better than sum-of-modified-Laplacian in most of cases. Later, MMAM is used to fused multi-focus image by combined structure-driven fused regions and depth information of blurred images. Experimental results demonstrate that the proposed algorithm outperforms the state-of-the-art fusion algorithms on image quality and objective fusion criteria. This paper firstly proposes the concept and computational processing of MMAM, which provides a new research direction and innovative idea for multi-focus image fusion base on filter, and MMAM can embedded into state-of-the-art fusion algorithm to achieve high quality multi-focus image fusion.