The work aims to solve the problems that the image information is easily lost in the current image fusion technology, and the edge and texture information of the source image cannot be better preserved, thus reducing the image resolution and visual quality and discouraging it from the clear, complete and accurate information description of targets, etc. The weighted image fusion scheme based on guided filtering coupled fractal dimension was proposed. Firstly, the source image was preprocessed, and the dynamic range of the image was improved by contrast enhancement. Secondly, the image was decomposed into low frequency part and high frequency part by wavelet transform. Then, the steerable filter was introduced to process the low frequency and high frequency components, so as to obtain the corresponding weights of low frequency and high frequency. The edge information of image could be well maintained. Thirdly, the local feature fractal dimension was extracted to obtain the microtexture feature. Finally, a weighted fusion scheme was defined, and the fusion was conducted according to the low-frequency and high-frequency weights to obtain the final fused image. The experimental data showed that, compared with the current commonly used image fusion algorithm, the proposed algorithm had better visual effects of fusion and kept the real information of the source images in a better manner. With respect to four quantitative analysis indicators (IE, MI, AG and STD), the proposed algorithm had more advantages. The proposed algorithm has good fusion quality, which has certain reference value in the field of image processing.