• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Intelligent automation and soft computing >Generic Evaluation Metrics for Hyperspectral Data Unmixing
【24h】

Generic Evaluation Metrics for Hyperspectral Data Unmixing

机译：高光谱数据分解的通用评估指标

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

We propose novel generic performance metric for hyperspectral unmixing techniques. This relative metric compares two abundance matrices. The first one represents the unmixing result. The second matrix can be either another unmixing result or the ground truth of the hyperspectral scene. This metric starts by computing coincidence matrices corresponding to the two abundance matrices, then the comparison is carried out by computing statistics of the number of pairs of data points that have high abundances with respect to the same endmember for the first unmixing approach, but have large abundance differences with respect to the same endmember for the second unmixing technique, or large differences in both. The main advantage of this metric approach is that there is no need to pair the endmembers of the two unmixing approaches. Rather, it assumes that the pixels, which are considered as different/same material by one unmixing approach should also be considered different/same material by the other. Our initial experiments on synthetic dataset have indicated the appropriateness of the proposed performance measures to assess unmixing techniques. Finally, the proposed metric are assessed using real dataset, and existing hyperspectral unmixing techniques.
机译：我们提出了针对高光谱解混技术的新型通用性能指标。此相对度量比较两个丰度矩阵。第一个表示分解结果。第二矩阵可以是另一个分解结果，也可以是高光谱场景的地面实况。该度量首先从计算与两个丰度矩阵相对应的重合矩阵开始，然后通过对第一种分解方法计算相对于同一端成员具有高丰度的数据点对的数量进行统计，从而进行比较。第二种拆解技术相对于同一端构件的丰度差异，或两者之间的差异较大。这种度量方法的主要优点是，无需将两种解混方法的末端成员配对。而是，假定通过一种解混合方法被视为不同/相同材料的像素也应被另一种方法也视为不同/相同材料。我们在合成数据集上的初步实验表明，提出的性能指标可用于评估分解技术。最后，使用实际数据集和现有的高光谱解混技术对提出的指标进行评估。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号