宋文宣;彭代锋;

• 1:南京信息工程大学遥感与测绘工程学院

摘要(Abstract)：

针对传统变化检测方法依赖特征工程且自动化程度不高的问题，提出了一种基于改进全卷积网络的变化检测方法，可自动学习多层次特征图，实现端到端的变化检测。首先，将两期影像输入到两个共享权重的编码器以分别提取多维度特征图，并构造差值特征图以有效融合变化信息；然后，利用扩张卷积模块增加感受野以有效捕捉多尺度变化信息；最后，通过解码器层逐步增大特征图分辨率的同时恢复影像细节信息，并利用sigmoid层生成最终变化图。通过高分辨率遥感影像变化检测实验表明，该方法可显著降低变化检测虚检率和漏检率，提高变化检测的精度和可靠性。

关键词(KeyWords)： 变化检测;全卷积网络;多层次特征图;编码器;解码器

Abstract:

Keywords:

基金项目(Foundation): 国家自然科学基金项目(41801386);; 江苏省自然科学基金项目(BK20180797)

作者(Authors): 宋文宣;彭代锋;

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