基于多尺度区域粒度分析的遥感图像分割  

Remote Sensing Image Segmentation Based on a Multiresolution Region Granularity Analysis Method

作　　者：郑晨[1] 孙丁茜[2] 陈晓惠[3] 

机构地区：[1]河南大学数学与信息科学学院,河南开封475000 [2]东南大学数学系,江苏南京211189 [3]河南大学图书馆,河南开封475000

出　　处：《光谱学与光谱分析》2013年第7期1912-1916,共5页Spectroscopy and Spectral Analysis

基　　金：国家自然科学基金项目(41001286;41001251;41001256;41101425);河南省基础与前沿技术研究计划项目(132300410150)资助

摘　　要：针对高分辨率遥感图像中不同地物具有粒度差异的特点,提出了一种多尺度区域粒度分析的图像分割方法。该方法首先使用均值漂移得到图像各尺度上的初始过分割区域,然后通过考虑区域大小和区域间上下文关系进行粒度分析,最后利用马尔科夫随机场模型对图像的粒度信息和光谱信息进行建模,得到分割结果。用平朔地区SPOT5和泰州航拍等遥感图像进行了实验,并与若干考虑光谱特征的分割方法进行了对比,结果表明提出的方法能有效地提高分割精度。Remote sensing image has abundant granularity information. In order to utilize this information, a muhiresolution re- gion granularity analysis method is proposed in the present paper for image segmentation. The proposed method firstly uses the mean shift to obtain the initial over-segmented regions at each resolution of the image, and then extracts the granularity informa- tion bascd on the region size and the region context, the Markov random field is employed to provide the final segmentation result by modeling the spectrum information and the granularity information. The SPOT5 remote sensing images of Pingshuo and the aerial image of Taizhou were tested to evaluate the proposed method. Compared with other spectrum-based methods, our method shows a better performance and results improved the segmentation accuracy.

关 键 词：分割 粒度 马尔科夫随机场 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]