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Small UAV Based Multi-Viewpoint Image Registration for Extracting the Information of Cultivated Land in the Hills and Mountains

机译:基于小型无人机的多视点图像配准提取山丘耕地信息

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The amount of arable land in southern China is reduced due to land degradation and soil erosion. Arable land change by remote sensing technology is the most economical and efficient way to relieve the pressure of agricultural production. Therefore, we present a small unmanned aerial vehicle (U A V) based multi-viewpoint image registration method for extracting the information of arable changes in hills and mountains. Three major contributions of our method are included: (i) feature point sets were extracted by SURF; (ii) reliable correspondence was established by mixture-feature finite mixture model (MFMM); (iii) Lz-minimizing estimate (L2E) based energy function with double geometric constraints was used to estimate the transformation function. Compared with five state-of-the-art methods, our method shows better performances in most cases.
机译:由于土地退化和水土流失,中国南部的耕地减少了。遥感技术改变耕地面积是减轻农业生产压力的最经济,最有效的方法。因此,我们提出了一种基于小型无人机的多视点图像配准方法,用于提取丘陵和山区的耕地变化信息。我们方法的三个主要贡献包括:(i)通过SURF提取特征点集; (ii)通过混合特征有限混合模型(MFMM)建立了可靠的对应关系; (iii)使用具有双重几何约束的基于Lz最小化估计(L2E)的能量函数来估计变换函数。与五种最新方法相比,我们的方法在大多数情况下显示出更好的性能。

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