Abstract: Traditional fusion methods cannot fully extract the details of visible and infrared images, and it is hard to determine the fusion weights. An adaptive image fusion method based on bilateral filters is thus proposed. First, an improved bilateral filter is employed to decompose the source images into local details, unique details, and base parts. Second, the local details are merged based on the energy of image edges to retain details to the maximum. The base parts are fused using an adaptive regularization parameter based on local energy. Finally, the fused image is obtained. Experimental results indicate that the fused image obtained by the proposed fusion method has a better visual effect, higher contrast, and clearer edge details. In comparison with other four methods, the Mutual Information(MI), Feature Mutual information(FMI), Standard Deviation(SD), Mount of edge Information(Q), and Mean of the new approach have increased by 22.6%, 5.7%, 0.7%, 30.4%, 14.2%, and 18.4%, respectively. Therefore, the proposed image fusion method has a better performance than other methods in terms of both subjective and objective evaluation.

Key words: visibleandinfraredimage, imagefusion, imageenergyofedge, localenergy