Accurate and efficient image alignment is the core problem in the research of panoramic stitching nowadays. This paper proposes a local-adaptive image alignment method based on triangular facet approximation, which directly manipulates the matching data in the camera coordinates, and therefore rises superior to the imaging model of cameras. A more robust planar transformation model is proposed and extended to be local-adaptive via combining it with two weighting strategies. By approximating the scene as a combination of adjacent triangular facets, the planar and spherical triangulation strategies are introduced to more efficiently align normal and fisheye images respectively. The efficiency of the proposed method are verified through the comparative experiments on several challenging cases both qualitatively and quantitatively.

The fast algorithm for satellite visibility is very important in many applications, particularly in the real-time simulation environments. In this paper, a novel algorithm, true anomaly iteration compensation (TAIC) algorithm, is proposed to predict the visibility of the elliptical orbits' satellites. A main property of our algorithm is that it could avoid solving the transcendental equation: Kepler Equation, therefore the computation of the algorithm is very small. Furthermore, a compensation method is used to yield more accurate results. The excellent performance of the algorithm is illustrated by the numerical results. For TAIC algorithm, the error of visibility- time is about 0.21% and the error of the entry-access time instant and the exit-access time instant is about 0.79 seconds.