摘要
基于遥感技术的变化检测是遥感应用的一个重要方面。传统基于遥感的变化检测方法一般是利用光谱信息,较少注意多时相图像间的光谱特征相关关系分析。本文运用地统计学的伪交叉变差函数(Pseudo Cross Vario-gram)计算多时相图像纹理,定量表达多时相图像间的空间相关关系,并将得到的多时相纹理信息与光谱信息一起用于多时相变化检测。实验结果表明,加入多时相纹理信息可以显著提高变化检测精度,是一种有效的方法。
Change detection based on remote sensing is one of the important aspects in remote sensing application. Traditional remote sensing change detection methods usually use spectral information alone and ignore the correlation between multitemporal images. This paper proposes to quantitatively express the temporal correlation between multitemporal images by multivariate texture, which is measured by pseudo cross variogram, a geostatistical tool. The obtained muhitemporal texture, as an additional band, is incorporated into muhitemporal classification for change detection. The results show that, compared with the result of using spectral information alone, the inclusion of multitemporal classification in change detection can significantly improve the overall accuracy. The experimental results also validate the effectiveness of the proposed method.
出处
《国土资源遥感》
CSCD
2009年第3期35-40,共6页
Remote Sensing for Land & Resources
关键词
伪交叉变差函数
多时相纹理
变化检测
Pseudo cross variogram
Muhitemporal texture
Change detection
