  How to use multiple optical satellite images to recover the 3D scene
structure is a challenging and important problem in the remote sensing field.
Most existing methods in literature have been explored based on the classical
RPC (rational polynomial camera) model which requires at least 39 GCPs (ground
control points), however, it is not trivial to obtain such a large number of
GCPs in many real scenes. Addressing this problem, we propose a hierarchical
reconstruction framework based on multiple optical satellite images, which
needs only 4 GCPs. The proposed framework is composed of an affine dense
reconstruction stage and a followed affine-to-Euclidean upgrading stage: At the
affine dense reconstruction stage, an affine dense reconstruction approach is
explored for pursuing the 3D affine scene structure without any GCP from input
satellite images. Then at the affine-to-Euclidean upgrading stage, the obtained
3D affine structure is upgraded to a Euclidean one with 4 GCPs. Experimental
results on two public datasets demonstrate that the proposed method
significantly outperforms three state-of-the-art methods in most cases.
