邓继忠, 任高生, 兰玉彬, 黄华盛, 张亚莉. 基于可见光波段的无人机超低空遥感图像处理[J]. 华南农业大学学报, 2016, 37(6): 16-22. DOI: 10.7671/j.issn.1001-411X.2016.06.003
    引用本文: 邓继忠, 任高生, 兰玉彬, 黄华盛, 张亚莉. 基于可见光波段的无人机超低空遥感图像处理[J]. 华南农业大学学报, 2016, 37(6): 16-22. DOI: 10.7671/j.issn.1001-411X.2016.06.003
    DENG Jizhong, REN Gaosheng, LAN Yubin, HUANG Huasheng, ZHANG Yali. Low altitude unmanned aerial vehicle remote sensing image processing based on visible band[J]. Journal of South China Agricultural University, 2016, 37(6): 16-22. DOI: 10.7671/j.issn.1001-411X.2016.06.003
    Citation: DENG Jizhong, REN Gaosheng, LAN Yubin, HUANG Huasheng, ZHANG Yali. Low altitude unmanned aerial vehicle remote sensing image processing based on visible band[J]. Journal of South China Agricultural University, 2016, 37(6): 16-22. DOI: 10.7671/j.issn.1001-411X.2016.06.003

    基于可见光波段的无人机超低空遥感图像处理

    Low altitude unmanned aerial vehicle remote sensing image processing based on visible band

    • 摘要:
      目的  探讨低成本的可见光超低空农业遥感平台提取与分析农情信息的可行性,为农用无人机精准施药与农情监测提供技术支持。
      方法  以仅包含红光、蓝光和绿光的超低空可见光农田遥感图像为研究对象:首先利用张氏校正法获取相机的畸变矩阵,并校正图像;然后提取与分析图像的可见光植被指数;最后通过分析超低空可见光农田图像中植被与非植被的光谱特性,对可见光超低空遥感图像进行植被信息提取。
      结果  获得的农田植被提取图像很好地区分了植被与非植被。
      结论  基于可见光的超低空遥感农业信息获取系统应用具有可行性,可为构造低成本的可见光低空遥感监测系统提供参考。

       

      Abstract:
      Objective The feasibility of agricultural information extraction and analysis based on low cost agricultural visible band platforms with low altitude remote sensing was investigated to provide a technical support for precision spraying and monitoring with unmanned aerial vehicles (UAVs).
      Method A series of tests were conducted to study the visible light remote sensing images that contained only red, blue and green bands. First, Zhang correction method was used to get the distortion matrix of camera and to correct images. Then, the visible vegetation indices were extracted from corrected images. Finally, by analyzing the spectral characteristics of low altitude farmland visible images of vegetation and non-vegetation, the vegetation information was extracted from visible band based on low altitude remote sensing images.
      Result Vegetation was separated from non-vegetation area with farmland vegetation index extraction.
      Conclusion  Agricultural information acquisition system based on visible light low altitude remote sensing is applicable and can provide a reference for the development of low cost visible band monitoring system with low altitude remote sensing.

       

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