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

Rongbin Wang, Chao Zeng, Pingxiang Li, Huanfeng Shen
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引用次数: 15

Abstract

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.
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基于地图算法的Terra MODIS 5波段条纹噪声检测与校正
由于Terra MODIS波段5(1.230 ~ 1.250µm)的20个探测器中有1个存在噪声,因此在整个图像上存在尖锐且重复的条纹。对于MODIS定位数据来说,条纹是不规则的,有时甚至是不连续的,这给图像检索带来了难题。本文提出了一种提取条纹噪声的检测方法,并基于最大后验(MAP)算法对污染像素进行校正。在MAP方法中,基于线性图像噪声模型提出了似然概率密度函数,并采用Huber-Markov模型作为先验似然概率密度函数。采用梯度下降优化方法接收去条纹图像。该算法已在Terra MODIS 5波段定位图像上进行了测试。实验结果表明,该算法具有良好的性能。
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