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A simple measure of confidence for fuzzy land-cover classification from remote-sensing data

机译：基于遥感数据的模糊土地覆盖分类的置信度的简单度量

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摘要

Representing the quality of thematic maps derived from remote-sensing image classification is important in assessing its fitness for use. Conventional approaches to represent the quality in terms of accuracy need information from the reference data at the same scale. Error-prone or dubious reference data may have an impact on the assessment of quality. Therefore, measures that complement the conventional accuracy measures are required to represent the quality. Uncertainty and confidence are such measures that do not require reference data. Few studies have been attempted to derive pixel-level confidence. However, these measures are not widely adopted by the remote-sensing community due to their limitations. In this article, a simple measure of confidence is derived to represent the quality of fuzzy classification. To derive the confidence value for a pixel, two values, viz. first highest class membership value as evidence and an associated degree of certainty, are required. When the difference between first and second highest membership values is used as degree of certainty in the proposed approach, the confidence measure derived is equal to the complement of existing measure of uncertainty, viz. confusion index in difference form.
机译：代表从遥感影像分类中得出的专题图的质量对于评估其适用性非常重要。用精度表示质量的常规方法需要来自相同规模的参考数据的信息。容易出错或可疑的参考数据可能会影响质量评估。因此，需要补充传统精度度量的度量来表示质量。不确定性和置信度是不需要参考数据的度量。很少有研究试图得出像素级置信度。然而，由于其局限性，这些措施并未被遥感界广泛采用。在本文中，得出了一种简单的置信度度量来表示模糊分类的质量。为了得出像素的置信度值，两个值，即。首先，需要最高的会员资格价值作为证据以及相关的确定性。当在建议的方法中将第一和第二最高隶属度值之间的差用作确定度时，得出的置信度度量等于现有不确定性度量的补充，即。差异形式的混淆指数。

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  • 来源
    《International journal of remote sensing》 |2014年第24期|8122-8137|共16页
  • 作者

    Prasad M. S. Ganesh; Arora Manoj K.;

  • 作者单位

    Natl Inst Engn, Dept Civil Engn, Mysore 570008, Karnataka, India;

    PEC Univ Technol, Chandigarh 160012, India;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
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