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- 2016
一种新的遥感影像变化检测方法
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Abstract:
针对地理国情监测中大幅面多时相遥感影像变化检测的需求，提出了一种基于卡方变换和样本选择的面向对象遥感影像变化检测方法。首先对多时相遥感影像进行多尺度分割获取像斑；然后，提取像斑的多维特征，采用基于卡方变换的特征融合方法计算像斑的加权差异度；最后，自适应选择训练样本，通过基于最大期望算法的贝叶斯阈值确定方法获取变化阈值，并对加权差异影像进行二值分割获取变化检测结果。以武汉市东湖高新技术开发区为例，利用多时相高分辨率遥感影像进行土地覆盖变化检测。试验结果表明，该方法可以克服全样本变化向量分析法及全样本卡方变换检测法难以满足阈值确定条件的不足，获得更准确的变化阈值，保证变化检测正确率高而又有效地降低漏检率，从而获得更好的变化检测结果，在地理国情监测中具有一定的应用价值
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