亚米级全色遥感影像云地检测算法研究

发布时间：2018-06-01 00:50

本文选题：云检测 + 大尺度自适应匹配阈值(LS-AMTH)　；参考：《光电子·激光》2017年07期

【摘要】：为解决现行云地检测算法不适用于亚米级全色遥感影像云地检测的问题,提出一种大尺度自适应匹配阈值(LS-AMTH,large-scale adaptive matching threshold)算法。算法构建包含光谱、纹理与边缘特征的特征参量集,利用提升算法对影像子块进行大尺度云地分类;之后对大尺度分类所得云地子块进行阈值的自适应匹配选择,最终实现像素级云地区域检测并统计云地占比。试验表明,针对亚米级全色影像,本文算法准确度达97.3%,在复杂云地混合区域取得良好检测效果。
[Abstract]:In order to solve the problem that the current cloud detection algorithm is not suitable for sub-meter panchromatic remote sensing image cloud detection, a large scale adaptive matching threshold LS-AMTHlarge-scale adaptive matching threshold) algorithm is proposed. The algorithm constructs feature parameter sets including spectral, texture and edge features, uses lifting algorithm to classify image subblocks on a large scale, and then adaptively matches the threshold values of cloud subblocks obtained from large-scale classification. Finally, the pixel level cloud area detection and statistics cloud area ratio. The experimental results show that the accuracy of this algorithm is 97.3 for sub-meter panchromatic images, and good detection results are obtained in the mixed regions of complex clouds and ground.
【作者单位】：中国科学院长春光学精密机械与物理研究所;中国科学院大学;
【基金】：国家“863”计划(2014AA7012019)资助项目
【分类号】：TP751

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