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首页> 外文期刊>International journal of remote sensing >Application of the wavelet transform for feature extraction in the analysis of hyperspectral laser-induced fluorescence data
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Application of the wavelet transform for feature extraction in the analysis of hyperspectral laser-induced fluorescence data

机译：小波变换在特征提取中在高光谱激光诱导的荧光数据分析中的应用

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摘要

Remote-sensing approaches for environmental protection and exploration have evolved rapidly in the last decade. Among the new operational tools, hyperspectral Fluorescent LiDAR System (FLS®) lidar has demonstrated a high sensitivity and the ability to function in complex environments for real-time, robust oil-spill monitoring on airborne or ship-borne analytical platforms. The capabilities of such analytical platforms include real-time analysis of laser-induced fluorescence (LIF) data. Although numerous examples of the application of signal theory to the analysis of hyperspectral data appear in the remote-sensing literature, the conventional data analysis strategies are not well adapted to the practical issues of the LIF applications. The aim of this article is to provide a new approach for LIF lidar analytical platforms, which is focused on the specifics of hyperspectral LIF data. The approach is based on structural data analysis and interpretation, through which more detailed spectral matching is performed. This article is based on a simulated experiment in which the spectra of actual seawater and well-known types of petroleum products were combined to demonstrate the wavelet-transform-based analysis of LIF data. The final part of the article demonstrates the application of the wavelet transform to the structural analysis of LIF data from field experiments for the detection and identification of oil products in difficult environmental conditions.
机译：在过去的十年中，环境保护和勘探的遥感方法发展迅速。在新的操作工具中，高光谱荧光LiDAR系统（FLS®）激光雷达具有很高的灵敏度，并具有在复杂环境中运行的能力，可在机载或舰载分析平台上进行实时，强大的溢油监控。这种分析平台的功能包括对激光诱导的荧光（LIF）数据进行实时分析。尽管在遥感文献中出现了将信号理论应用到高光谱数据分析中的众多例子，但是传统的数据分析策略并未很好地适应LIF应用的实际问题。本文的目的是为LIF激光雷达分析平台提供一种新方法，该方法着重于高光谱LIF数据的细节。该方法基于结构数据分析和解释，通过它进行更详细的光谱匹配。本文基于一个模拟实验，其中将实际海水和著名类型的石油产品的光谱相结合，以演示基于小波变换的LIF数据分析。本文的最后一部分演示了小波变换在现场实验中对LIF数据进行结构分析的应用，以在困难的环境条件下检测和识别石油产品。

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  • 来源
    《International journal of remote sensing》 |2013年第20期|7218-7235|共18页
  • 作者

    Innokenti Sobolev; Sergey Babichenko;

  • 作者单位

    Department of Computer Control, Tallinn University of Technology, Tallinn, Estonia;

    LDI Innovation, Tallinn, Estonia;

  • 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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