Measures for an Objective Evaluation of the Geometric Correction Process Quality
Measures for an Objective Evaluation of the Geometric Correction Process Quality
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DOI：
10.1109/lgrs.2008.2012441
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发表时间：
2009-04-01
影响因子：
4.8
通讯作者：
Corte-Real, Luis
中科院分区：
文献类型：
--
作者：
Goncalves, Hernani;Goncalves, Jose A.;Corte-Real, Luis
几何校正过程是遥感应用中的关键步骤。由于自动图像配准方法还远未得到广泛应用，因此这一过程通常是手动执行的，这在许多情况下是一项艰巨的任务。证明自动图像配准方法缺乏广泛应用的原因之一是缺乏对图像配准过程质量进行客观和自动分析的措施。残差的均方根（RMS）是该过程中通常使用的唯一定量评价，几何校正过程的最终验证是定性分析。因此，在“人”和自动图像配准过程中，需要对其质量进行客观评价。在这封信中，我们提出了几个措施的几何校正过程的客观评价，作为补充，传统的RMS的残差和目视检查。考虑了控制点分布和最常见的残差分布两种情况。我们打算通过拟议措施涵盖最常见的定性分析方面。这在自动图像配准方法的范围内特别重要，其中还需要对结果进行自动评估。
The geometric correction process is a crucial step in remote sensing applications. This process is frequently manually performed-which is a laborious task in many situations-as automatic image registration methods are still far from being broadly applied. One of the reasons that justify the absence of a broad application of automatic image registration methods is the lack of measures for an objective and automated analysis of the image registration process quality. The root mean square (RMS) of the residuals is the only quantitative evaluation which is generally used in this process, with the final validation of the geometric correction process being a qualitative analysis. Therefore, in both "human" and automatic image registration processes, an objective evaluation of its quality is required. In this letter, we propose several measures for an objective evaluation of the geometric correction process, as a complement to the traditional RMS of the residuals and visual inspection. Two scenarios of control point distribution and the most common residual distributions were considered. With the proposed measures, we intend to cover the most common qualitative analysis aspects. This has particular importance under the scope of automatic image registration methods, where an automatic evaluation of the results is also required.