用主成分分析研究QuickBird遥感图像变形机制

Deformation Mechanism of QuickBird Remote Sensing Image Using Principal Components Analysis

以深圳市区一景QuickBird Pan波段遥感图像(总行列数为26574×28606,对应15.944km×17.164km的实地范围)为研究对象,利用深圳市GPS虚拟参考网络定位系统,以厘米级精度测定了65个在图像上能有效识别的地面控制点三维坐标。计算65个控制点的重心点,在统计各控制点到重心点之间真实距离和在变形图像上对应距离偏差的基础上,分析可能影响QuickBird Pan波段遥感图像像点位移的主要因子。利用主成分分析从这些因子中提取影响图像变形的主成分,根据所得主成分建立QuickBird Pan波段遥感图像变形机制的定量估测模型,使图像变形估测精度得到一定改善。所得结果对研究高空间分辨率遥感图像变形纠正算法有一定参考价值。

With one scope of QuickBird panchromatic band remote sensing image（total rows and columns are 26 574 and 28 606,corresponding to the real region of 15.994 km×17.164 km） in Shenzhen urban area as research object,using the GPS virtual reference network positioning system of Shenzhen urban area to survey the three-dimensional coordinates of 65 GCPs which are easily recognized on the image,the precision of surveying GCPs is centimeter-level.Calculate the point of center of gravity of 65 GCPs.On the basis of statistic of the deviation between the real distance of each GCP to the point of center of gravity and the corresponding distance on deformed image,analyzing the main factors that possibly influence the pixel displacement of QuickBird panchromatic band remote sensing image.The principal components are extracted by using principal components analysis.The quantitative estimation model used to describe the deformation mechanism of QuickBird panchromatic band remote sensing image is established according to the principal components,which can improve the estimation precision of image deformation to a certainty.The result will have some reference value to research calibration algorithm of high spatial resolution remote sensing image.