首页> 外文会议>Image and Signal Processing for Remote Sensing XI >Assessment of signal-to-noise ratio of CHRIS/PROBA and other hyperspectral sensors using images acquired over the San Rossore (Italy) test site
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Assessment of signal-to-noise ratio of CHRIS/PROBA and other hyperspectral sensors using images acquired over the San Rossore (Italy) test site

机译:使用在圣罗索尔(意大利)测试现场获得的图像评估CHRIS / PROBA和其他高光谱传感器的信噪比

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摘要

Using several hyperspectral images acquired by various aerospace sensors over San Rossore (Italy) test site, different issues concerning the assessment of the noise amplitude, which affects the remotely sensed images, are investigated. An innovative algorithm, developed by the authors, is presented and its performance is discussed. This procedure analyses the bit-planes extracted from any monochromatic image in the hyperspectral data cube, then it assesses the randomness of every bit-plane, and computes the signal-to-noise ratio for each spectral channel. Differently from more traditional signal-to-noise ratio estimators, which need an homogeneous area in the concerned image to isolate noise contribution only, the new algorithm is almost insensitive to scene texture. Due to this property the developed method is able to process the image of any observed ground area. The paper discusses other possible sources of systematic disturbance (like stripe-noise, smear effect, and so forth), which may dim the quality of remotely sensed data. Finally, the behaviour of signal-to-noise ratio of CHRIS and other hyperspectral sensors like MIVIS and VIRS-200 is shown as function of wavelengths.
机译:利用在意大利圣罗索尔(San Rossore)测试现场的各种航空航天传感器获取的几幅高光谱图像,研究了与噪声幅值评估有关的不同问题,这些影响了遥感图像。提出了一种由作者开发的创新算法,并讨论了其性能。此过程分析从高光谱数据多维数据集中的任何单色图像提取的位平面,然后评估每个位平面的随机性,并计算每个光谱通道的信噪比。与更传统的信噪比估计器不同,后者需要在相关图像中均匀分布区域以仅隔离噪声贡献,而新算法几乎对场景纹理不敏感。由于这种特性,开发的方法能够处理任何观察到的地面区域的图像。本文讨论了系统干扰的其他可能来源(例如条带噪声,拖尾效应等),这些来源可能会使遥感数据的质量变暗。最后,CHRIS和其他高光谱传感器(如MIVIS和VIRS-200)的信噪比行为显示为波长的函数。

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