Bias-compensated RPCs for sensor orientation of high-resolution satellite imagery
Bias-compensated RPCs for sensor orientation of high-resolution satellite imagery
复制标题
DOI：
10.14358/pers.71.8.909
复制
发表时间：
2005-08-01
影响因子：
1.3
通讯作者：
Hanley, HB
中科院分区：
文献类型：
--
作者：
Fraser, CS;Hanley, HB
对高分辨率卫星图像（HRSI）的更高质量度量产品的需求正在增长，HRSI传感器和产品选项的数量正在增加。有一个更大的需要，以充分了解的潜力，甚至缺点替代摄影测量传感器的方向模型HRSI。到目前为止，有理函数已被证明是一个可行的替代模型的地理定位，并与最近的创新偏差补偿RPC光束法平差，它已被证明，传感器的方向，以子像素的水平，可以实现最小的地面控制。然而，关于偏置补偿有理多项式系数（RPC）的普遍适用性以及一般的有理函数的普遍适用性的问题仍然存在。本文的目的是证明广泛的适用性偏差补偿RPC的高精度地理定位立体HRSI。立体图像在山区地形的情况下，将具体解决，和实验测试的结果都伊科诺斯和QuickBird图像将提交。
The demand for higher quality metric products from high-resolution satellite imagery (HRSI) is growing, and the number of HRSI sensors and product options is increasing. There is a greater need to fully understand the potential and indeed shortcomings of alternative photogrammetric sensor orientation models for HRSI. To date, rational functions have proven to be a viable alternative model for geo-positioning, and with the recent innovation of bias-compensated RPC bundle adjustment, it has been demonstrated that sensor orientation to sub-pixel level can be achieved with minimal ground control. Questions have lingered, however, as to the general suitability of bias-compensated rational polynomial coefficients (RPCs), and indeed rational functions in general. The purpose of this paper is to demonstrate the wide applicability of bias-compensated RPCs for high-accuracy geopositioning from stereo HRSI. The case of stereo imagery over mountainous terrain will be specifically addressed, and results of experimental testing of both Ikonos and QuickBird imagery will be presented.