A technology for generation of space object optical image based on 3D point cloud model

The lack of the prior image data in the space exploration tasks makes it difficult to quantitatively test and evaluate the situation awareness and navigation algorithms based on the optical images. Accordingly, in this paper, we present an algorithm for generating the synthetic space object optical image based on the 3D point cloud model and the basic theory of the projective transformation. First, the 3D point cloud model of the space object and the optical camera model were constructed. Then, the corresponding pairs between all the pixels in the image plane and the space points of the 3D point cloud model were obtained via the basic theory of projective transformation, and subsequently the intensity of each pixel in the image plane was calculated by the lighting direction of its corresponding space point and the Lambertian reflection model, and finally the simulated image was generated. A great deal of simulation experiments demonstrate that the proposed algorithm can produce the more vivid simulated images rapidly than the traditional analytical image generation algorithm, and the generated images can be applied to testing and evaluating the typical space application algorithms qualitatively and quantitatively, such as ellipse fitting, crater detection, optical navigation landing on the planet, automated rendezvous and docking of spacecraft, 3D tracking of spacecraft, and so on. © 2020, Editorial Board of JBUAA. All right reserved.