Affine & scale-invariant heterogeneous pyramid features for automatic matching of high resolution pushbroom imagery from Chang’e 2 satellite

Abstract

The automatic feature extracting and matching for large amount of linear pushbroom imagery with higher and higher resolution is urgent and challenging in three dimensional reconstructions, remote sensing and mapping. Affine & scale-invariant heterogeneous pyramid feature is proposed in this paper, along with the new scale-invariant analysis method, the detecting of the key points, the affine & scale-invariant descriptor, the steering method of the matching, and the quasi-dense matching algorithm based on the extensive epipolar geometry. The automatic matching is devised for the linear pushbroom imagery. The whole process is executed on lunar images of the highest resolution of ~7 m/pixel (or ~1 m/pixel in the lower orbits) from the Chinese Chang’e 2 satellite, it runs robustly at present, and resulting in large amounts of well-distributed-correspondences with accuracy of 0.3 pixels and excellent reliability, which gives great support for the further exploration both on the Moon and the Earth.