The work aims to solve the problems as discontinuity and blurring effect of the fused image induced by neglecting the image details contained in the low frequency coefficients in the current image fusion algorithm in the process of fusion. An image fusion algorithm based on two-dimensional factor coupled with second-generation curvelet transform was proposed. Firstly, second-generation curvelet transform with multi-scale and multi-direction characteristics was used to decompose the source image rapidly to obtain the fine low-frequency and high-frequency coefficients of the source image. Two-dimensional factors were constructed by introducing the information entropy of low-frequency coefficients and regional variance characteristics. The main information and change degree of the image contained in low-frequency coefficients were measured, in order to complete the fusion of low-frequency coefficients. Subsequently, by means of the average gradient characteristics of high-frequency coefficients, the information fusion rules were established to complete the fusion of high-frequency coefficients, in order to further improve the detail information content of the fused image. Finally, the R, G and B values of the pixels were used to construct a color correction factor to correct the fused image in order to obtain the fused image with better color effect. The experimental results showed that, the proposed method had better detail expression ability than the current image fusion method, and the fused image had better clarity and visual effect. The proposed algorithm has better fusion quality and it can improve the contrast and resolution of the image, which has a certain reference value in the field of image processing.