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De-striping for MODIS Data via Wavelet Shrinkage

机译:通过小波收缩对MODIS数据进行去条纹

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MODIS measurements contain the striping signals in the longwave infrared bands because MODIS is a multi-detector sensor. We describe a wavelet method for recovery of MODIS data from its stripe signals. Our work is organized into four broad sections. Section 1 will introduce wavelet shrinkage method for de-noising noisy data, compare the character of the wavelet method and the FFT method in de-noising processing. The objective of section 2 is to find out the scale of MODIS stripe by the wavelet analysis for MODIS stripe data using continuous wavelet transforms. Section 3 analyses Stripe data pattern for the MODIS level 1B stripe data, present the wavelet shrinkage method for MODIS level 1B data. Section 4 will provide a comparing for MODIS cloud product and atmospheric profile product between the original data and de-striped data. We can find that there's been an improvement in MODIS cloud product and atmospheric profile product after de-striping. And we can get more understanding for the stripe regular pattern.
机译:由于MODIS是多探测器传感器,因此MODIS测量包含长波红外波段中的条带信号。我们描述了一种从条带信号中恢复MODIS数据的小波方法。我们的工作分为四个主要部分。第1节将介绍小波收缩法对噪声数据进行去噪,比较小波方法和FFT方法在去噪处理中的特点。第2节的目的是通过使用连续小波变换对MODIS条带数据进行小波分析来找出MODIS条带的规模。第三部分分析了MODIS 1B级数据的条带数据模式,介绍了MODIS 1B级数据的小波收缩方法。第4节将比较原始数据和去条纹数据中的MODIS云产品和大气廓线产品。我们发现,去条纹后,MODIS云产品和大气廓线产品有了改进。并且我们可以对条纹常规模式有更多的了解。

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