Abstract
Abstract. High resolution, optical satellite sensors are boosted to a new era in the last few years, because satellite stereo images at half meter or even 30cm resolution are available. Nowadays, high resolution satellite image data have been commonly used for Digital Surface Model (DSM) generation and 3D reconstruction. It is common that the Rational Polynomial Coefficients (RPCs) provided by the vendors have rough precision and there is no ground control information available to refine the RPCs. Therefore, we present two relative orientation methods by using corresponding image points only: the first method will use quasi ground control information, which is generated from the corresponding points and rough RPCs, for the bias-compensation model; the second method will estimate the relative pointing errors on the matching image and remove this error by an affine model. Both methods do not need ground control information and are applied for the entire image. To get very dense point clouds, the Semi-Global Matching (SGM) method is an efficient tool. However, before accomplishing the matching process the epipolar constraints are required. In most conditions, satellite images have very large dimensions, contrary to the epipolar geometry generation and image resampling, which is usually carried out in small tiles. This paper also presents a modified piecewise epipolar resampling method for the entire image without tiling. The quality of the proposed relative orientation and epipolar resampling method are evaluated, and finally sub-pixel accuracy has been achieved in our work.
Highlights
Accompanied by the emergence of dense image matching method like Semi-Global Matching (SGM) method (Hirschmuller, 2008), more and more researchers shift their interests to use photogrammetric method for Digital Surface Model (DSM) generation and 3D reconstruction
We find that the Rational Polynomial Coefficients (RPCs) quality of the QuickBird test data is very poor, because it causes about 45 pixels relative pointing errors before the relative orientation
The interval between each epipolar curve and the sample distance along the epipolar segment are both equal to the ground sample distance (GSD) of the left image
Summary
Accompanied by the emergence of dense image matching method like Semi-Global Matching (SGM) method (Hirschmuller, 2008), more and more researchers shift their interests to use photogrammetric method for Digital Surface Model (DSM) generation and 3D reconstruction. Epipolar resampling procedure is important because the corresponding points locate on the same row in the generated epipolar images, which reduces the search range of matching form 2D to 1D space. This character improves the efficiency of dense image matching significantly. As Kim (2000) explained in his work, the epipolar curves of satellite pushbroom sensor are more like hyperbola curves than straight lines, and the epipolar pairs only exist locally It is well-known, that the RPCs provide a direct relationship between object and image space.
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