首页> 外文会议>Multispectral, hyperspectral, and ultraspectral remote sensing technology, techniques and applications VI >Retrieval of the Pixel Component Temperatures from Multi-Band Thermal Infrared Image Using Bayesian Inversion Technique
【24h】

Retrieval of the Pixel Component Temperatures from Multi-Band Thermal Infrared Image Using Bayesian Inversion Technique

机译:使用贝叶斯反演技术从多波段热红外图像中检索像素分量温度

获取原文
获取原文并翻译 | 示例

摘要

Majority of pixels, in the nature, are non-isothermal in three dimensions, especially for the pixels in meter-scale, tens-meter-scale or hundreds-meter-scale which are paid extensive attention by the researchers in geoscience field. The three-dimensional non-isothermal phenomenon even exists in some pixels in centimeter-scale. For the geosciencific researches, it is significant to determine the component temperatures of a pixel precisely. The airborne WSIS (Wide Spectrum Imaging Spectrometer) data with VNIR (visible-near infrared), SWIR (short-wave infrared) and TIR (thermal infrared) bands were used in the study. First, the components of all the pixels in the image were determined by the linear mixing method. Second, each component emissivity of each pixel was calculated based on an emissivity priori knowledge base. Last, a temperature and emissivity separation algorithm was used to inverse the mean temperature of each pixel, regarded as initial value, the Planck function was linearized to construct a multi-band equation set, and the component temperatures of every pixel were inversed by the Bayesian retrieval technique. The results suggest that the inversion precision of the pixel component temperatures is improved effectively by the Bayesian retrieval technique with the assistance of the VNIR and SWIR hyperspectral remote sensing data.
机译:本质上,大多数像素在三个维度上都是非等温的,特别是对于米级,数十米级或数百米级的像素,这是地球科学领域研究人员广泛关注的。三维非等温现象甚至存在于厘米级的某些像素中。对于地球科学研究而言,精确确定像素的组件温度非常重要。在研究中使用了带有VNIR(近红外),SWIR(短波红外)和TIR(热红外)波段的机载WSIS(宽光谱成像光谱仪)数据。首先,通过线性混合方法确定图像中所有像素的成分。其次,基于发射率先验知识库计算每个像素的每个分量发射率。最后,采用温度和发射率分离算法对每个像素的平均温度进行求逆,将其作为初始值,对普朗克函数进行线性化,以构建一个多波段方程组,并通过贝叶斯逆对每个像素的成分温度进行求逆。检索技术。结果表明,借助贝叶斯检索技术,借助VNIR和SWIR高光谱遥感数据,有效提高了像素分量温度的反演精度。

著录项

  • 来源
  • 会议地点 New Delhi(IN)
  • 作者单位

    Key Lab of Spatial Active Opto-Electronic Techniques, Shanghai Insitute of Technical Physics, Chinese Academy of Sciences, Shanghai 200083, China;

    Key Lab of Spatial Active Opto-Electronic Techniques, Shanghai Insitute of Technical Physics, Chinese Academy of Sciences, Shanghai 200083, China;

    Key Lab of Spatial Active Opto-Electronic Techniques, Shanghai Insitute of Technical Physics, Chinese Academy of Sciences, Shanghai 200083, China;

    Key Lab of Spatial Active Opto-Electronic Techniques, Shanghai Insitute of Technical Physics, Chinese Academy of Sciences, Shanghai 200083, China;

    Key Lab of Spatial Active Opto-Electronic Techniques, Shanghai Insitute of Technical Physics, Chinese Academy of Sciences, Shanghai 200083, China;

    Key Lab of Spatial Active Opto-Electronic Techniques, Shanghai Insitute of Technical Physics, Chinese Academy of Sciences, Shanghai 200083, China;

    Key Lab of Spatial Active Opto-Electronic Techniques, Shanghai Insitute of Technical Physics, Chinese Academy of Sciences, Shanghai 200083, China;

    Shanghai Key Laboratory of Criminal Scene Evidence, Institute of Forensic Science, Shanghai Public Security Bureau, Shanghai 200083, China;

  • 会议组织
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Thermal infrared multispectral data; Bayesian inversion technique; component temperatures;

    机译:热红外多光谱数据;贝叶斯反演技术;元件温度;

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