Diffusion-based three-dimensional reconstruction of complex surface using monocular vision

Three-dimensional (3D) reconstruction based on optical diffusion has certain significant advantages, such as its capacity for high-precision depth estimation with a small lens, distant-object depth estimation, a monocular vision basis, and no required camera or scene adjustment. However, few mathematical models to relate the depth information acquired using this technique to the basic principles of intensity distribution during optical diffusion have been proposed. In this paper, the heat diffusion equation of physics is applied in order to construct a mathematical model of the intensity distribution during optical diffusion. Hence, a high-precision 3D reconstruction method with optical diffusion based on the heat diffusion equation is proposed. First, the heat diffusion equation is analyzed and an optical diffusion model is introduced to explain the basic principles of the diffusion imaging process. Second, the novel 3D reconstruction method based on global heat diffusion is proposed, which incorporates the relationship between the depth information and the degree of diffusion. Finally, a simulation involving synthetic images and an experiment using five playing cards are conducted, with the results confirming the effectiveness and feasibility of the proposed method.