融合像素—多尺度区域特征的高分辨率遥感影像分类算法  

Fusion of pixel-based and multi-scale region-based features for the classification of high-resolution remote sensing image

作　　者：刘纯[1,2] 洪亮[1,2,3,4] 陈杰[3] 楚森森 邓敏[3] 

机构地区：[1]云南师范大学旅游与地理科学学院,云南昆明650500 [2]西部资源环境地理信息技术教育部工程研究中心,云南昆明650500 [3]中南大学地球科学与信息物理学院地理信息系,湖南长沙410083 [4]中国矿业大学江苏省资源环境信息工程重点实验室,江苏徐州221000

出　　处：《遥感学报》2015年第2期228-239,共12页NATIONAL REMOTE SENSING BULLETIN

基　　金：国家自然科学基金项目(编号:41201463;41201428);国家重点基础研究发展计划(973计划)(编号:2012CB719906);国家高技术研究发展计划(863计划)(编号:2012AA121400);江苏省资源环境信息工程重点实验室开放基金资助项目(编号:JS201301);云南省教育厅基金项目(编号:2011Y311)

摘　　要：针对基于像素多特征的高分辨率遥感影像分类算法的"胡椒盐"现象和面向对象影像分析方法的"平滑地物细节"现象,提出了一种融合像素特征和多尺度区域特征的高分辨率遥感影像分类算法。(1)首先采用均值漂移算法对原始影像进行初始过分割,然后对初始过分割结果进行多尺度的区域合并,形成多尺度分割结果。根据多尺度区域合并RMI指数变化和分割尺度对分类精度的影响,确定最优分割尺度。(2)融合光谱特征、像元形状指数PSI(Pixel Shape Index)、初始尺度和最优尺度区域特征,并对多类型特征进行归一化,最后结合支持向量机(SVM)进行分类。实验结果表明该算法既能有效减少基于像素多特征的高分辨率遥感影像分类算法的"胡椒盐"现象,又能保持地物对象的完整性和地物细节信息,提高易混淆类别(如阴影和街道,裸地和草地)的分类精度。With the improvement of spatial resolution of remote sensing image, the details, geometrical structure and texture features of ground objects have been better presented. As the same object type has different spectra or different object types have same spectrum, the statistical separability of different land cover classes in spectral domain is reduced, which is a great challenge to the traditional classification methods based on pixel-features for high spatial resolution remote sensing image. Classification accu- racies based on pixel classification methods are improved by fusing pixel texture, structure and shape features. But the pixel-based multi-feature classification methods generally have the shortcomings of ＂salt and pepper＂ effect and computational complexity. In recent years, the Object Based Image Analysis （OBIA） method has been widely concerned. The basic characteristic of OBIA is homogeneous regions as processing units. OBIA method can solve ＂salt and pepper＂ problem within traditional methods, and over- comes the shortcomings among pixel-based classification methods. However, a large segmentation scale in OBIA leads to lose detail and present ＂excessive smoothing＂ phenomenon. In view of the ＂salt and pepper＂ phenomenon of pixel-based multi-feature classi- fication methods and the ＂excessive smoothing＂ phenomenon of OBIA, a classification method which fused pixel-based multi- feature and multi-scale region-based features is proposed in this paper. （ 1 ） The over-segment image objects are obtained by mean shift algorithm. Then regions are merged based on the original over-segmentation results through multi-scale, and the multi-scale segmentation results are obtained. According to change of multi-scale regions merged index-RMI and the correlation between classi- fication accuracy and segmentation scale, when the RMI change is small, the adjacent regions are merged, and the RMI change is significant, best segmentation results are obtained in the optimal scale and the adjacent r

关 键 词：高分辨率遥感影像 融合 多尺度 像元形状指数 支持向量机 

分 类 号：P237[天文地球—摄影测量与遥感] TP751.1[天文地球—测绘科学与技术]