Evaluation of Optimal Segmentation Scale with Object-oriented Method in Remote Sensing
面向对象的遥感影像最优分割尺度评价

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.