基于面特征的遥感图像几何校正模型  

The Area-based Geometric Correction Model for Remote Sensing Image

作　　者：龙腾飞[1,2] 焦伟利[1] 王威[1] 

机构地区：[1]中国科学院遥感与数字地球研究所,北京100094 [2]中国科学院大学北京100049

出　　处：《测绘学报》2013年第4期540-545,共6页Acta Geodaetica et Cartographica Sinica

基　　金：国家自然科学基金(61271013);国家863计划(2012BAH27B05)

摘　　要：传统的遥感图像几何校正模型是基于控制点建立的。然而在很多情况下,图像的面特征比点特征更易自动提取。提出面特征之间距离的定义及算法,在此基础上利用控制面建立误差方程,实现基于面特征的几何校正。以Land-sat、ALOS和Quickbird影像为例进行了试验,结果表明,本文的方法可用于不同的卫星影像和成像模型。当控制资料不含粗差时,利用控制面和控制点的校正精度基本一致,可达到1个像素以内;当控制资料含有粗差时,基于面特征的几何校正模型比基于点特征的几何校正模型具有更强的容错能力。Traditional remote sensing image geometric correction model is based on control points. However, the areal features in images can be easier extracted automatically than the point features in many cases. The definitions and algorithms of the distance between the area features and how to establish the error equation using ground control area are proposed, and geometric correction based on areal features is achieved. Landsat, ALOS and QuickBird images are used as examples for the test and the experimental results to show that the proposed method can be used for different satellite images and imaging models. The calibration accuracies in the test are basically the same, both are less than one pixel, when the control data does not contain gross errors for control area and control point, while the area-based geometric correction model is more fault-tolerant than the point-based model when the control data contains gross errors.

关 键 词：遥感图像 几何校正模型 面特征 距离 

分 类 号：P236[天文地球—摄影测量与遥感]