Image Fusion of Infrared and Visible Images Based on Residual Significance

To make the fusion image show more image details and to obtain a better image visual effect, a fusion method based on residual significance is proposed. First, the infrared image is analyzed using residual significance to obtain its significance coefficients. Then, the source images are decomposed using a dual-tree complex wavelet transform, and the low- and high-frequency components are fused according to different fusion rules. Finally, the fusion image is reconstructed using the inverse transformation of a dual-tree complex wavelet. Experimental results showed that the fusion method proposed in this paper produced higher quality images and better visual effects than those of the traditional fusion method.