Fast Global Motion Estimation on Android-based Software-defined Satellite
Yijun Lin, Junxing Hu, Fengge Wu, Junsuo Zhao · 2019
Recently, although advanced satellite can collect massive image data, the efficiency of information extraction is still lacking due to low-quality and redundancy of data, and limited transmission bandwidth worsens this situation. As the result, researchers start to focus on software-defined satellite. Through directly deploying image processing applications on a space-based computing platform, satellite's capabilities can be flexibly changed, expanded or enhanced. Under such a trend, this paper proposes a global motion estimation system which attempts to reduce data redundancy in satellite videos. Our work consists of two stages: first, adaptively feature matching and optical flow are combined to estimate global motion. Following this, we give the transform formula between homography matrices in different resolution images, thus algorithm can be faster executed at a smaller search space. The proposed system runs on the Android platform, which is easy to be programmed, ported and updated. It is validated on the newest software-defined satellite TianZhi-1, and shows outstanding results under real experimental environment.