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首页> 外文期刊>IEEE Transactions on Geoscience and Remote Sensing >Thin Cloud Removal Based on Signal Transmission Principles and Spectral Mixture Analysis
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Thin Cloud Removal Based on Signal Transmission Principles and Spectral Mixture Analysis

机译：基于信号传输原理和谱混合分析的薄云去除

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摘要

Cloud removal is an important goal for enhancing the utilization of optical remote sensing satellite images. Clouds dynamically affect the signal transmission due to their different shapes, heights, and distribution. In the case of thick opaque clouds, pixel replacement has been commonly adopted. For thin clouds, pixel correction techniques allow the effects of thin clouds to be removed while retaining the remaining information in the contaminated pixels. In this paper, we develop a new method based on signal transmission and spectral mixture analysis for pixel correction which makes use of a cloud removal model that considers not only the additive reflectance from the clouds but also the energy absorption when solar radiation passes through them. Data correction is achieved by subtracting the product of the cloud endmember signature and the cloud abundance and rescaling according to the cloud thickness. The proposed method has no requirement for meteorological data and does not rely on reference images. Our experimental results indicate that the proposed approach is able to perform effective removal of thin clouds in different scenarios.
机译：去除云是提高光学遥感卫星图像利用率的重要目标。由于云的形状，高度和分布不同，它们会动态影响信号传输。对于不透明的厚云，通常采用像素替换。对于薄云，像素校正技术可以去除薄云的影响，同时将剩余信息保留在受污染的像素中。在本文中，我们开发了一种基于信号传输和光谱混合分析的像素校正新方法，该方法利用了除云模型，该模型不仅考虑了来自云的附加反射率，还考虑了太阳辐射穿过云时的能量吸收。通过减去云端成员签名和云丰度的乘积并根据云厚度重新缩放，可以实现数据校正。所提出的方法不需要气象数据，也不依赖于参考图像。我们的实验结果表明，所提出的方法能够在不同情况下有效去除薄云。

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