南极光学卫星遥感影像大规模无控区域网平差方法

Block Adjustment of Large-Scale Domestic Optical Satellite Remote Sensing Imagery Without GCPs in the Antarctic

针对南极测图困难地区,传统人工制图方法往往难以保证有利的观测条件,提出一种利用高分辨率光学卫星遥感影像进行大规模无控区域网平差的方法。该方法主要包括基于虚拟控制点的平差模型构建、多级粗差探测与剔除策略、利用GPU加速的大规模平差方程的稳健和快速解算等关键步骤。为验证所提方法的有效性,利用南极地区长条带39景资源三号卫星影像进行实验分析。实验结果表明,稀疏矩阵储存技术可以有效减少内存需求,同时利用GPU并行计算的方法可以解决大规模平差参数求解效率问题。经过区域网平差后,所提方法的精度达到亚像素级别,完全满足制图接边要求。

Traditional manual mapping methods face crucial challenges in ensuring favorable observation conditions in difficult mapping areas in the Antarctic.This study proposes a large-scale block adjustment(BA)method without ground control points(GCP)using high-resolution optical satellite remote sensing images.This method mainly includes constructing an adjustment model based on virtual control points(VCPs),implementing a multilevel gross error detection and elimination strategy,and providing a robust and fast solution of large-scale BA equations accelerated by a GPU device.To validate the effectiveness of the proposed method,an experimental analysis was conducted using 39 images obtained from the ZiYuan-3 satellite images in the Antarctic.The experimental results indicate that sparse matrix storage technology can effectively reduce memory requirements,and the GPU parallel computing method can address efficiency problem in solving large-scale adjustment parameters.The accuracy of the proposed method reaches the subpixel level after the BA procedure,fully meeting the requirements of cartographic mosaicing.