Parameter selection for segmentation in object-oriented classification of remotely sensed imagery
In object-oriented classification of remote sensing imagery, image segmentation is the first step and its quality has significant effect on resulting classification. The quality of image segmentation is always controlled by usersupplied parameters. However, there is not a common way to guide the user selecting a suitable parameter for image segmentation. This paper focuses on the problem of parameter selection for region-growing method, which is one of the most popular segmentation techniques in object-oriented classification of remotely sensed imagery. The presented method selects the suitable parameters by means of training sample areas of each class chosen from an image. The parameter selection method is verified in an experiment of object-oriented classification.
classification image parameter remote sensing segmentation
Shukui Bo Xinchao Han
Department of Computer Science and Application Zhengzhou Institute of Aeronautical Industry Manageme Department of Computer Seienee and Teehnology Zhongyuan University of Technology Zhengzhou, China
国际会议
长沙
英文
2046-2049
2010-05-11（万方平台首次上网日期，不代表论文的发表时间）