Recent constellations of satellites, including the Skysat constellation, are able to acquire bursts of images. This new acquisition mode allows for modern image restoration techniques, including multi-frame super-resolution. As the satellite moves during the acquisition of the burst, elevation changes in the scene translate into noticeable parallax. This parallax hinders the results of the restoration. To cope with this issue, we propose a novel parallax estimation method. The method is composed of a linear Plane+Parallax decomposition of the apparent motion and a multi-frame optical flow algorithm that exploits all frames simultaneously. Using SkySat L1A images, we show that the estimated per-pixel displacements are important for applying multi-frame super-resolution on scenes containing elevation changes and that can also be used to estimate a coarse 3D surface model.
翻译:包括 Skysat 星座在内的近期卫星星座能够获得图像的连发。 这种新的获取模式允许现代图像恢复技术,包括多框架超分辨率。 随着卫星在获取爆破期间的移动,场面的海拔变化会转化成显著的parllax。 这个参数会阻碍修复的结果。 为了解决这个问题,我们提出了一个新型的parlax估计方法。 方法由线性Plane+Parlarlax对表面运动的分解和同时利用所有框架的多框架的多框架光学流算法组成。 我们使用 SkySat L1A 图像显示, 估计的每像素迁移对于在包含高度变化的场景上应用多框架超分辨率非常重要, 并且也可以用来估计粗微的 3D 表面模型。