Abstract:

To obtain a high quality fused image consistent with characteristics of human vision, a novel image fusion method for infrared and visual images guided by visual saliency is proposed. First of all, for the given infrared and visible images, the modified Manifold Ranking algorithm is utilized to extract their visual salient areas respectively. Then, source images are decomposed in different scales and directions by Non-subsampled Contourlet Transform to obtain low frequency information and high frequency information. And results of visual saliency detection are used to guide the fusion rule of low frequency subband coefficients. Besides, the high frequency subband coefficients are fused owing to the local standard deviation criterion. Finally, the fused image is obtained by performing inverse Non-subsampled Contourlet Transform. Experimental results demonstrate that the proposed algorithm can not only assure the final fused images with clear detail information, but also highlight the infrared objects accurately, which presents a good vision effect and effectively enhances recognition probability of infrared and visible compound systems.

Key words: image fusion, infrared and visible images, non-subsampled contourlet, visual saliency