Fast Multispectral Fusion and High-Precision Interdetector Image Stitching of Agile Satellites Based on Velocity Vector Field

When the targets are distributed irregularly, it is of great significance to quickly acquire color images with a wide field by agile satellite. Attributed to the changing of the three-axis attitude and Earth’s rotation, there are misalignment and distortion during the processing of imaging by agile satellite. It makes the fusion of interband images slower and the stitching of interdetector images poorer. In this article, a rigorous velocity vector field (VVF) model is established through tracing rays between the image and the object. It calculates the misalignment among the images of bands in each detector to align and fuse multispectral images. Based on the reference image selected by VVF, the fused images are stitched with the method of leveraging line-point consistency. Finally, both field and in-orbit experiments are conducted. The time of calculating misalignment in image fusion with VVF is 13.19% of the minimum time of the traditional registration algorithm. In image stitching, our RMSE values are 1.15, which is the smallest among the RMSE values of SIFT, SURF, and SPW. In preserving linear structure, compared with SPW, the values of
${E_{\text {dis}}}$
,
${E_{\text {err}}}$
, and
${E_{\text {cross}}}$
, respectively, reduce 60%, 50%, and 50%. The results show that images of the agile satellite can be fast fused and precisely stitched using VVF while correcting distortion. The compensation strategy of the VVF provides a theoretical basis for the agile satellite in image fusion and stitching.