An Epipolar Resampling Method for Multi-View High Resolution Satellite Images Based on Block

Shuhan Du,Bijie Xu,Hui Yi,Xiangning Chen,Feng Zhao,Decheng Wang

doi:10.1109/access.2021.3133664

Abstract

As the basis of stereo observation, epipolar resampling is a critical technology for 3D reconstruction. With the development of the 3D reconstruction using multi-view satellite images, the epipolar resampling of the multi-view satellite images has become a new challenging problem. In this paper, we propose an epipolar resampling method for multi-view high resolution satellite images based on block. Firstly, we establish the relationship between the vertical parallax and image block size for the epipolar resampling based on block. Using this relationship, we can choose the block size to limit the maximum vertical parallax in epipolar resampling. Secondly, we use the rational function model (RFM) to generate virtual corresponding points for fundamental matrix estimation, so image pairs with large stereo angles and poor consistency in multi-view satellite images which are difficult to extract feature matching point can be rectified. Experiments with multi-view satellite images demonstrated the universality and effectiveness of the proposed method. All the image pairs in the multi-view satellite image dataset were rectified successfully. The average epipolar resampling error is only 0.25 pixels when we rectify the multi-view satellite images acquired by WorldView-3 with the block size of 3000*3000 pixels, significantly less than the similar method.

Highlights

The increasing number of high resolution optical remote sensing satellite has collected a large number of images in the past decade
Rapid and fully automatic 3D reconstruction from multi-view satellite images is being interested in remote sensing since it can be extremely useful for urban planning, information extraction, and global situational awareness [1,2,3]
In a rectified epipolar image pair, the search for conjugate points in stereo matching can be limited to horizontal lines

Summary

Introduction

The increasing number of high resolution optical remote sensing satellite has collected a large number of images in the past decade. They have high revisit frequency over a certain area, which can provide multi-view stereo images for three dimensional (3D) reconstruction. As the basis of stereo observation, epipolar resampling is one of the key technologies for 3D reconstruction [4,5,6]. In a rectified epipolar image pair, the search for conjugate points in stereo matching can be limited to horizontal lines. By reducing the search space from two dimensional space into one dimensional, the efficiency of the stereo matching in 3D reconstruction can be improved greatly. Many valuable stereo matching algorithms such as the semi-global matching (SGM) and more global matching (MGM) have been developed based on the epipolar resampling [7,8,9]

Methods

Discussion

Conclusion