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Toward Optimal Destriping of MODIS Data Using a Unidirectional Variational Model

机译:使用单向变分模型实现MODIS数据的最佳去条纹

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摘要

Images acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard Terra and Aqua exhibit strong detector striping. This artifact is common to most pushbroom scanners and affects both visual interpretation and radiometric integrity of remotely sensed data. A considerable effort has been made to remove stripe noise and reduce its impact on high-level products. Despite the variety of destriping algorithms proposed in the literature, complete removal of stripes without signal distortion is yet to be overcome. In this paper, we tackle the striping issue from a variational angle. Basic statistical assumptions used in previous techniques are replaced by a much realistic geometrical consideration on the striping unidirectional variations. The resulting algorithm is tested on Aqua and Terra MODIS data contaminated with severe stripes and is shown to provide optimal qualitative and quantitative results.
机译:Terra和Aqua上的中等分辨率成像光谱仪(MODIS)采集的图像显示出很强的检测条纹。这种伪影对于大多数推扫式扫描仪而言都是常见的,并且会影响视觉解释和遥感数据的辐射完整性。为了消除条带噪声并减少其对高级产品的影响,已经做出了相当大的努力。尽管在文献中提出了各种各样的去条纹算法,但是仍需要克服完全去除条纹而没有信号失真的问题。在本文中,我们从变化的角度解决了条带化问题。先前技术中使用的基本统计假设已由对条带单向变化的非常实际的几何考虑所取代。所得算法在受严重条纹污染的Aqua和Terra MODIS数据上进行了测试,并显示出最佳的定性和定量结果。

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