Stereo rectification of pushbroom satellite images by robustly estimating the fundamental matrix

Abstract

ABSTRACT Stereo rectification is one of the most important steps for stereo matching and subsequently for digital surface model generation from satellite stereo images. This study proposes a new framework to rectify two pushbroom images along the epipolar geometry in order to omit the vertical parallax between two images. Here, we assume the interior and relative parameters between the two pushbroom images are not known and the images can be taken at different dates. Traditional stereo rectification methods of pushbroom images require metadata such as rational polynomial coefficients (RPCs), parameters of physical sensor model or ground control points (GCPs). In this study, we develop an image-based framework for stereo rectification, which works without the need for such data. In the proposed framework, the correspondences are densely extracted by a tilling strategy, and then the fundamental matrix is robustly estimated by two geometric constraints. Both affine and projective fundamental matrices could be used for stereo rectification from pushbroom stereo images. The results on IRS P5, World view III, GeoEye and IKONOS stereo pairs as well as on multi-date stereo images demonstrate that the pushbroom images are rectified with sub-pixel accuracy.