面向对象的遥感影像最优分割尺度评价

遥感影像分割决定了后续分类的精度,鉴于目前分割技术评价的研究缺乏且局限于主观判断的现状,以定量方法确定最优分割尺度。利用Definiens平台面向对象的分割算法,将组成对象的像素灰度值的标准差作为衡量对象内同质性的标准,用与邻域的平均差分的绝对值作为对象间的异质性度量变量,同时考虑面积权重的影响；根据上述3个评价指标,在考虑多光谱影像的基础上,构造了平均分割评价指数；基于该评价指数,以优度实验法对QuickBird多光谱影像进行了研究,并确定了不同地物类型的最优分割尺度。最后,利用平均对象匹配指数对评价结果进行了验证,并对评价方法的可行性进行了探讨。

Evaluation of Optimal Segmentation Scale with Object-oriented Method in Remote Sensing

Image segmentation determines the accuracy of subsequent classification in remote sensing.In consideration of the research lacking of evaluation about segmentation technology and limitation of the mainly subjective method currently,quantitative method is used to select optimal segmentation scale in this paper.With object|oriented segmentation algorithm of Definiens software,standard deviation of all pixels from an image object is used as the homogeneity measured criteria in object,absolute value of  mean difference to neighbors is served as the variable of heterogeneity between objects,weighting coefficient of the object area is also considered.With the three evaluation criteria,thinking of multispectral images,the average segmentation evaluation index is constructed.Based on the evaluation index,with goodness test method,QucikBird multispectral image is used to be researched,and the optimal segmentation scales of different surface features are concluded.At last,the average object fit index is used to verify evaluation results,and the feasibility of the evaluation method is discussed.