MRF框架下的区域增长模型在城镇识别中的应用

A Region Growing Model Under the Framework of MRF for Urban Detection

提出一种MRF框架下以过分割区域为基本生长单位的区域增长模型,并以其实现城镇识别。该模型首先通过纹理分析和滤波运算得到初始种子点,然后由均值漂移算法运算过分割区域,并将种子点对应的区域设为种子区域,最后,从种子区域开始,根据MRF框架下提出的增长准则,得到最终的城镇识别结果。对QuickBird和IKONOS遥感影像的实验表明,该模型能有效地识别出影像中的城镇区域。

A region growing model under the framework of MRF is proposed for urban detection and the basic unit of the model is over segmentation region.This model firstly obtains the initial seed points by texture analysis.Then the over segmentation regions are got by mean shift（MS） algorithm and the regions that include seed points are set to seed regions.At last,starting from the seed regions,the finally result of urban is detected through a growing criterion under the framework of MRF.The experiments of QuickBird and IKONOS demonstrate that our model can effectively detect the urban area from the remote sensing images.