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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:基于直方图的自适应滤波器对无人机装载的多光谱摄像机采集的NDVI图像进行去条纹

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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:无人机(UAV)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。但是,得到的植被指数图像(例如归一化差异植被指数(NDVI))具有不可忽略的条纹噪声,并严重干扰了植被信息的提取。在这封信中,在条纹状NDVI图像的灰度直方图和傅立叶频谱中观察到了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,然后根据原始NDVI图像的直方图曲线的主要峰值和谷值等特征,设计了一种用于傅立叶光谱中的条带噪声去除的自适应滤波器。将此自适应滤波器应用于相应的傅立叶光谱图像,我们实现了自动有效的条纹噪声去除,而无需任何人工干预。基于视觉判断和定量评估,与改进的高通滤波器和二维Weiner滤波器相比,所提出的自适应滤波器在保持图像保真度和清晰度方面表现出更好的性能。

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