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A variational approach for the destriping of modis data

机译:一种用于分装Modis数据的变体方法

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The Moderate Resolution Imaging Spectrometer (MODIS) monitors the earth in 36 spectral bands using a cross-track double-sided continuously rotating scan mirror. The imperfect calibration of the linear arrays of detectors and additional random noise in the internal calibration system induce detector-to-detector stripes, mirror side stripes and noisy stripes visible in most emissive bands. This artefact affects seriously the visual quality and radiometric integrity of measured data. Several approaches including Fourier filtering, wavelet analysis and statistical techniques such as moment matching or histogram matching have been used to reduce striping on MODIS Data. Despite an extensive and diverse destriping literature, most techniques display residual stripes if not strong distortion from the original image. In this paper, we introduce a robust destriping methodology based on a variational approach.
机译:中分辨率成像光谱仪(MODIS)使用跨轨双面连续旋转扫描镜监视36个光谱带中的地球。检测器线性阵列的不完全校准和内部校准系统中的其他随机噪声会导致在大多数发射波段中可见的检测器到检测器条纹,镜侧条纹和噪声条纹。这种伪影会严重影响测量数据的视觉质量和辐射完整性。包括傅里叶滤波,小波分析和统计技术(例如矩匹配或直方图匹配)在内的几种方法已用于减少MODIS数据上的条带化。尽管有广泛而多样的描述文学,但大多数技术都显示出残留条纹,即使这些条纹与原始图像相比没有强烈的失真。在本文中,我们介绍了一种基于变分方法的健壮的分条方法。

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