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首页> 外文期刊>IEEE Geoscience and Remote Sensing Letters >Histogram-Based Autoadaptive Filter for Destriping NDVI Imagery Acquired by UAV-Loaded Multispectral Camera
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Histogram-Based Autoadaptive Filter for Destriping NDVI Imagery Acquired by UAV-Loaded Multispectral Camera

机译：基于直方图的Autoadaptive滤波器，用于由UAV加载的多光谱相机获取的NDVI图像

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摘要

Combinations of unmanned aerial vehicles (UAVs) and multispectral sensors provide low-cost approaches for detailed spatiotemporal vegetation studies. However, the resulting vegetation index images such as normalized difference vegetation index (NDVI) have unignorable stripe noise and seriously disturb the extraction of vegetation information. In this letter, the similar frequency phenomena caused by stripe noise were observed in the gray-scale histogram and the Fourier spectrum of a striped NDVI image. Thus, we tried establishing the empirical quantitative relationship between them, and then designed an autoadaptive filter for stripe noise removal in Fourier spectrum according to the characteristics including the dominant peak and troughs of the histogram curve of the raw NDVI image. Applying this autoadaptive filter to the corresponding Fourier spectrum image, we achieved automatic and effective stripe noise removal without any manual interference. Based on visual judgment and quantitative evaluation, the proposed autoadaptive filter demonstrated by far the better performance in retaining image fidelity and intelligibility than the improved high-pass filter and 2-D Weiner filter.
机译：无人驾驶飞行器（无人机）和多光谱传感器的组合为详细的时空植被研究提供了低成本的方法。然而，由此产生的植被指数图像如归一化差异植被指数（NDVI）具有不可源性的条纹噪声，并严重扰乱植被信息的提取。在这封信中，在灰度直方图和条纹NDVI图像的傅里叶谱中观察到由条纹噪声引起的类似频率现象。因此，我们尝试建立它们之间的经验定量关系，然后设计了一种根据未加工NDVI图像的直方图曲线的主导峰值和槽的特性设计了用于傅立叶谱中的条纹噪声去除的自动覆盖滤波器。将此Autoadaptive过滤器应用于相应的傅立叶频谱图像，我们实现了自动和有效的条纹噪声除去，无需任何手动干扰。基于视觉判断和定量评估，所提出的Autoadtive过滤器在迄今为止，在更好的性能方面，在比改进的高通滤波器和2-D Weiner滤波器上保持图像保真度和可懂度。

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