Relative Orientation and Modified Piecewise Epipolar Resampling for High Resolution Satellite Images

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.

Point Cloud and Digital Surface Model Generation From High Resolution Multiple View Stereo Satellite Imagery

“…The parameters of the registration are reused to calculate a translation in image space for the RPCs refinement. Gong and Fritsch (2017) proposed the relative biascompensated model without GCPs. Several tie points are detected first.…”

“…As well as the absolute bias-compensated bundle block adjustment, the relative model also estimates an additional affine model to compensate the relative bias for each image, and at least 4 to 6 ground control points are needed (Fraser and Hanley, 2005). In our previous research (Gong and Fritsch, 2017), the accuracy of the relative bias-compensated model with virtual ground control information can reach sub-pixel level.…”

“…We resample the epipolar images along those epipolar segments from bottom to top and align the epipolar segment pair of stereo image to the same row. The details are referred to (Gong and Fritsch, 2017).…”

A Double Epipolar Resampling Approach to Reliable Conjugate Point Extraction for Accurate Kompsat-3/3A Stereo Data Processing

“…The conjugate image points were used to generate quasi-GCPs by the space intersection using the RPCs, followed by the reprojection of the quasi-GCPs back to the stereo data to analyze the errors in the image space. The errors were minimized by applying bias compensation to the RPCs [31][32][33]. In contrast, for the proposed approach, we generated coarse epipolar images using the raw RPCs, followed by image matching with different methods and template sizes.…”