The work aims to propose an algorithm for reconstructing high dynamic range (HDR) images based on low dynamic range (LDR) images, in order to expand the dynamic range of images more easily and effectively in high dynamic range imaging technology (HDRI). Based on the convolutional deep neural network model of expanded convolutional layer, an image fusion algorithm based on various illumination and exposed LDR image groups in the same scene was proposed to establish a new model of HDR image. Through the proposed mapping relationship between LDR and HDR with different bit depths, the chain structure was used to complete the reconstruction from LDR image to HDR image. Through the proposed HDRI model, the dynamic range of the image is broadened and the physical light information recovery capability is improved. Compared with the traditional algorithm, the method proposed in this study can reduce the amount of computation and better restore the scene with high dynamic range.