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首页> 外文会议>International symposium on multispectral image processing and pattern recognition >A Parallel Method of Atmospheric Correction for Multispectral High Spatial Resolution Remote Sensing Images
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A Parallel Method of Atmospheric Correction for Multispectral High Spatial Resolution Remote Sensing Images

机译：多光谱高分辨率遥感影像的大气校正并行方法

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摘要

The remote sensing image is usually polluted by atmosphere components especially like aerosol particles. For the quantitative remote sensing applications, the radiative transfer model based atmospheric correction is used to get the reflectance with decoupling the atmosphere and surface by consuming a long computational time. The parallel computing is a solution method for the temporal acceleration. The parallel strategy which uses multi-CPU to work simultaneously is designed to do atmospheric correction for a multispectral remote sensing image. The parallel framework's flow and the main parallel body of atmospheric correction are described. Then, the multispectral remote sensing image of the Chinese Gaofen-2 satellite is used to test the acceleration efficiency. When the CPU number is increasing from 1 to 8, the computational speed is also increasing. The biggest acceleration rate is 6.5. Under the 8 CPU working mode, the whole image atmospheric correction costs 4 minutes.
机译：遥感图像通常被大气成分污染，特别是像气溶胶颗粒。对于定量遥感应用，基于辐射传递模型的大气校正可通过消耗较长的计算时间来获得反射率，从而将大气与地面解耦。并行计算是时间加速度的一种解决方法。使用多CPU并行工作的并行策略旨在对多光谱遥感图像进行大气校正。描述了平行框架的流程和大气校正的主要平行主体。然后，利用中国高分二号卫星的多光谱遥感图像测试了加速效率。当CPU数量从1增加到8时，计算速度也在增加。最大加速度为6.5。在8 CPU工作模式下，整个图像的大气校正需要4分钟。

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