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Terra MODIS band 5 Stripe noise detection and correction using MAP-based algorithm

机译:基于基于MAP的算法的Terra MODIS band 5条带噪声检测和校正

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Since 1 of the 20 detectors in Terra MODIS band 5 (1.230∼1.250 µm) are noisy, there are sharp and repetitive stripes over the entire image. As for MODIS geolocated data, the stripes are irregular and sometimes uncontinuous, it brings a difficult problem to the image retrieving process. This paper presents a detection method to extract the stripe noise, and a maximum a posteriori (MAP) based algorithm to correct the contaminated pixels. In the MAP method, the likelihood probability density function (PDF) is proposed based on a linear image noise model, and a Huber-Markov model is employed as the prior PDF. The gradient descent optimization method is used to receive the destriped image. The proposed algorithm has been tested using a Terra MODIS band 5 geolocated image. The experimental results demonstrate that the proposed algorithm performs well.
机译:由于Terra Modis带5(1.230~1.250μm)中的20个检测器中的1个是嘈杂的,因此整个图像上有尖锐和重复的条纹。对于Modis Geolocated数据,条纹是不规则的,有时是不连续的,它对图像检索过程带来了难题。本文提出了一种提取条纹噪声的检测方法,以及基于后的后验(MAP)的算法来校正受污染的像素。在地图方法中,基于线性图像噪声模型提出了似然概率密度函数(PDF),并且使用Huber-Markov模型作为先前的PDF。梯度下降优化方法用于接收DATRIPED图像。已经使用Terra Modis频带5 Geolocated图像测试了所提出的算法。实验结果表明,所提出的算法表现良好。

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