Combined Geometric Positioning and Performance Analysis of Multi-Resolution Optical Imageries from Satellite and Aerial Platforms Based on Weighted RFM Bundle Adjustment

Wenping Song,Changling Niu,Xiaohua Tong,Yanmin Jin,Shijie Liu,Zhen Ye

doi:10.3390/rs13040620

Abstract

Combined geometric positioning using images with different resolutions and imaging sensors is being increasingly widely utilized in practical engineering applications. In this work, we attempt to perform the combined geometric positioning and performance analysis of multi-resolution optical images from satellite and aerial platforms based on weighted rational function model (RFM) bundle adjustment without using ground control points (GCPs). Firstly, we introduced an integrated image matching method combining least squares and phase correlation. Next, for bundle adjustment, a combined model of the geometric positioning based on weighted RFM bundle adjustment was derived, and a method for weight determination was given to make the weights of all image points variable. Finally, we conducted experiments using a case study in Shanghai with ZiYuan-3 (ZY-3) satellite imagery, GeoEye-1 satellite imagery, and Digital Mapping Camera (DMC) aerial imagery to validate the effectiveness of the proposed weighted method, and to investigate the positioning accuracy by using different combination scenarios of multi-resolution heterogeneous images. The experimental results indicate that the proposed weighted method is effective, and the positioning accuracy of different combination scenarios can give a good reference for the combined geometric positioning of multi-stereo heterogeneous images in future practical engineering applications.

Highlights

Published: 9 February 2021The rapid development of sensor technology has led to the rapid improvement of multi-source high-resolution remote sensing imagery, including satellite imagery and aerial imagery [1,2,3,4,5]
[39] determined the geometric positioning accuracy that is achievable by integrating IKONOS and QuickBird satellite stereoscopic images with aerial images acquired in Tampa Bay, Florida. [40] demonstrated the feasibility of highprecision geometric positioning using a combination of Spot-5, QuickBird, and Kompsat-2 images based on a rigorous sensor model (RSM). [41] explored the geometric performance of the integration of aerial and QuickBird images in Shanghai, China. [42] proposed the intersection method to improve the accuracy of 3D positioning using heterogeneous satellite stereo images including two KOMPSAT-2 and QuickBird images covering the same area
In this work, aiming at providing a reference for the combined geometric positioning of multi-stereo heterogeneous images, we attempt to perform the combined geometric positioning and performance analysis of multi-resolution optical images from satellite and aerial platforms based on weighted rational function model (RFM) bundle adjustment, including four major processing steps: pre-processing, image matching, weighted bundle adjustment, and accuracy analysis

Summary

Introduction

Published: 9 February 2021The rapid development of sensor technology has led to the rapid improvement of multi-source high-resolution remote sensing imagery, including satellite imagery and aerial imagery [1,2,3,4,5]. High-precision geometric positioning depends highly on high-performance sensor structures and parameters to achieve the geometric transformation, or a large number of ground control points (GCPs) to construct the constraints between images [17,18,19,20] Such geometric positioning methods, rely heavily on the strictly confidential platform position and attitude parameters and the availability of a sufficient number of GCPs, especially for satellite imagery, but are time-consuming and expensive. Rely heavily on the strictly confidential platform position and attitude parameters and the availability of a sufficient number of GCPs, especially for satellite imagery, but are time-consuming and expensive To solve this problem, in recent years, much attention has been paid to geometric positioning without GCPs in applications involving multi-source data acquisition platforms. Laser altimetry data can be adopted to Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations

Methods

Results

Conclusion