...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Remote Sensing >An Assessment of Polynomial Regression Techniques for the Relative Radiometric Normalization (RRN) of High-Resolution Multi-Temporal Airborne Thermal Infrared (TIR) Imagery
【24h】

An Assessment of Polynomial Regression Techniques for the Relative Radiometric Normalization (RRN) of High-Resolution Multi-Temporal Airborne Thermal Infrared (TIR) Imagery

机译：高分辨率多时空机载热红外（TIR）图像的相对辐射归一化（RRN）多项式回归技术的评估

获取原文
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Thermal Infrared (TIR) remote sensing images of urban environments are increasingly available from airborne and satellite platforms. However, limited access to high-spatial resolution (H-res: ~1 m) TIR satellite images requires the use of TIR airborne sensors for mapping large complex urban surfaces, especially at micro-scales. A critical limitation of such H-res mapping is the need to acquire a large scene composed of multiple flight lines and mosaic them together. This results in the same scene components (e.g., roads, buildings, green space and water) exhibiting different temperatures in different flight lines. To mitigate these effects, linear relative radiometric normalization (RRN) techniques are often applied. However, the Earth’s surface is composed of features whose thermal behaviour is characterized by complexity and non-linearity. Therefore, we hypothesize that non-linear RRN techniques should demonstrate increased radiometric agreement over similar linear techniques. To test this hypothesis, this paper evaluates four (linear and non-linear) RRN techniques, including: (i) histogram matching (HM); (ii) pseudo-invariant feature-based polynomial regression (PIF_Poly); (iii) no-change stratified random sample-based linear regression (NCSRS_Lin); and (iv) no-change stratified random sample-based polynomial regression (NCSRS_Poly); two of which (ii and iv) are newly proposed non-linear techniques. When applied over two adjacent flight lines (~70 km2) of TABI-1800 airborne data, visual and statistical results show that both new non-linear techniques improved radiometric agreement over the previously evaluated linear techniques, with the new fully-automated method, NCSRS-based polynomial regression, providing the highest improvement in radiometric agreement between the master and the slave images, at ~56%. This is ~5% higher than the best previously evaluated linear technique (NCSRS-based linear regression).
机译：机载和卫星平台越来越多地提供城市环境的热红外（TIR）遥感图像。但是，要获得高空间分辨率（H-res：〜1 m）TIR卫星图像的机会有限，则需要使用TIR机载传感器来绘制大型复杂的城市表面，尤其是在微尺度上。这种H-res映射的一个关键限制是需要获取由多条飞行线组成的大型场景并将它们拼接在一起。这导致相同的场景组件（例如，道路，建筑物，绿地和水）在不同的飞行路线中呈现出不同的温度。为了减轻这些影响，经常应用线性相对辐射归一化（RRN）技术。但是，地球表面由一些特征组成，这些特征的热行为以复杂性和非线性为特征。因此，我们假设非线性RRN技术应证明比类似线性技术具有更高的辐射一致性。为了验证这一假设，本文评估了四种（线性和非线性）RRN技术，包括：（i）直方图匹配（HM）; （ii）基于伪不变特征的多项式回归（PIF_Poly）; （iii）无变化分层的基于随机样本的线性回归（NCSRS_Lin）; （iv）无变化分层的基于随机样本的多项式回归（NCSRS_Poly）;其中（ii和iv）是新提出的非线性技术。当在TABI-1800机载数据的两条相邻飞行线（〜70 km 2 ）上应用时，视觉和统计结果表明，这两种新的非线性技术都比先前评估的线性技术改善了辐射一致性，并且新的全自动方法，基于NCSRS的多项式回归，在主图像和从图像之间的辐射一致性方面提供了最大的改进，约为56％。这比先前评估的最佳线性技术（基于NCSRS的线性回归）高约5％。

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