Abstract
Abstract. The quality of the 3D model reconstructed using multi-view satellite image depends on the quality of the image. To evaluate the geometric quality of the satellite image, we proposed a method to evaluate the geometric distortion for satellite images and defined the deviation coefficient as a metric to evaluate the bending degree of a curve. After projecting a ground grid consisting of straight lines into the image space, the geometric distortion of the image can be evaluated quantitatively by calculating the deviation coefficients of the projection trajectories. Experiments have been carried out with three datasets obtained by JiLin-1, GaoFen-2, and WorldView-3 respectively. The results show that the proposed method can used to evaluate the geometric quality of satellite images effectively, and this evaluation method will be useful in image selecting in 3D reconstruction using multi-view satellite images.
Highlights
In recent years, with the rapid development of high resolution optical remote sensing satellites, satellite image resolution, spectrum and data acquisition capabilities have been continuously enhanced
We propose a new method to evaluate the geometric quality of images that can be used for satellite image selecting in 3D reconstruction
We establish a ground grid consist of a series of special straight lines in the ground space; we project the ground grid into the image plane using the satellite sensor model; the geometric quality of satellite images are evaluated by analyzing the projection trajectories of the ground grid
Summary
With the rapid development of high resolution optical remote sensing satellites, satellite image resolution, spectrum and data acquisition capabilities have been continuously enhanced. To promote the research of 3D reconstruction using highresolution satellite images, IARPA conducted the IARPA Multi-View Stereo 3D Mapping Challenge and released the corresponding IARPA MVS3DM dataset in 2016. By modifying the Satellite Stereo Pipeline (S2P) developed by De, et al (De Franchis et al, 2014), Facciolo, et al (Facciolo et al, 2017) proposes a solution that can reconstruct high quality 3D models from multi-view satellite images. In the follow-up studies, Gong, et al (Gong and Fritsch, 2018) proposed a method to generate 3D point clouds and digital surface models (DSMs) from multi-view satellite images. They select images according to the incidence angle and acquisition date. We establish a ground grid consist of a series of special straight lines in the ground space; we project the ground grid into the image plane using the satellite sensor model (rational function model); the geometric quality of satellite images are evaluated by analyzing the projection trajectories of the ground grid
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