The comparison index:: A tool for assessing the accuracy of image segmentation
The comparison index:: A tool for assessing the accuracy of image segmentation
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DOI：
10.1016/j.jag.2006.10.002
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发表时间：
2007-08-01
影响因子：
7.5
通讯作者：
Volk, M.
中科院分区：
文献类型：
--
作者：
Moeller, M.;Lymburner, L.;Volk, M.
应用于遥感数据的分割算法提供了关于景观对象在一系列尺度上的大小、分布和背景的有价值的信息。然而，需要定义良好且鲁棒的验证工具来评估分割结果的可靠性。需要这样的工具来评估图像分割是基于“真实的”对象（诸如场边界）还是基于图像分割算法的伪影。这些工具可以用来提高可靠性的任何土地利用/土地覆盖分类或景观分析，是基于图像segments.The验证算法在本文中开发的目的是：（a）本地化和量化分割不准确性;和（B）允许整体上的分割结果的评估。第一个目标是实现使用对象度量，使量化的拓扑和几何对象的差异。第二个目标是通过将这些对象度量组合成“比较指数”来实现的。这允许不同分割结果的相对比较。该方法演示了如何比较指数Cl可以用来指导试错技术，使识别的分割尺度H接近最佳。一旦这个规模已经确定了一个更详细的检查的CI-H图可以用来精确地确定什么H值和相关的参数设置将产生最准确的图像分割results.The程序适用于分割Landsat场景在农业领域在萨克森安哈尔特州，德国。分割是使用“分形网络进化方法”生成的，该方法在eCognition软件中实现。(C)2006 Elsevier B. V.保留所有权利。
Segmentation algorithms applied to remote sensing data provide valuable information about the size, distribution and context of landscape objects at a range of scales. However, there is a need for well-defined and robust validation tools to assessing the reliability of segmentation results. Such tools are required to assess whether image segments are based on 'real' objects, such as field boundaries, or on artefacts of the image segmentation algorithm. These tools can be used to improve the reliability of any land-use/ land-cover classifications or landscape analyses that is based on the image segments.The validation algorithm developed in this paper aims to: (a) localize and quantify segmentation inaccuracies; and (b) allow the assessment of segmentation results on the whole. The first aim is achieved using object metrics that enable the quantification of topological and geometric object differences. The second aim is achieved by combining these object metrics into a 'Comparison Index'. which allows a relative comparison of different segmentation results. The approach demonstrates how the Comparison Index Cl can be used to guide trial-and-error techniques, enabling the identification of a segmentation scale H that is close to optimal. Once this scale has been identified a more detailed examination of the CI-H- diagrams can be used to identify precisely what H value and associated parameter settings will yield the most accurate image segmentation results.The procedure is applied to segmented Landsat scenes in an agricultural area in Saxony-Anhalt, Germany. The segmentations were generated using the 'Fractal Net Evolution Approach', which is implemented in the eCognition software. (C) 2006 Elsevier B.V. All rights reserved.