Due to the unideal effects of those common multi-source focus image fusion algorithms, in this essay we propose a multi-focus image fusion algorithm based on sparse representation and orthogonal matching pursuit (OMP), and demonstrate the results of the corresponding multi-source focus image fusion experiments by MATLAB. Compared with the fused images of the above several common algorithms by evaluating subjectively and objectively, the results suggest that the multi-focus image fusion algorithm based on sparse representation and orthogonal matching pursuit (OMP) present higher mutual information, minimum distorted values and higher Q
ab / f
values which indicate that the fused image by this algorithm can obtain more image information with a smaller distortion from the original (image?), so as to get a better image but cost much more time.