It has been discovered that image motions and optical flows usually become much more nonlinear and anisotropic in space-borne cameras with large field of view, especially when perturbations or jitters exist. The phenomenon arises from the fact that the attitude motion greatly affects the image of the three-dimensional planet. In this paper, utilizing the characteristics, an optical flow inversion method is proposed to treat high-accurate remote sensor attitude motion measurement. The principle of the new method is that angular velocities can be measured precisely by means of rebuilding some nonuniform optical flows. Firstly, to determine the relative displacements and deformations between the overlapped images captured by different detectors is the primary process of the method. A novel dense subpixel image registration approach is developed towards this goal. Based on that, optical flow can be rebuilt and high-accurate attitude measurements are successfully fulfilled. In the experiment, a remote sensor and its original photographs are investigated, and the results validate that the method is highly reliable and highly accurate in a broad frequency band.
RDMO-SLAM: Real-time Visual SLAM for Dynamic Environments using Semantic Label Prediction with Optical Flow
