赣州稀土矿山高分辨率遥感影像分割的最优尺度选取  

Optimal Scale Selection Research of High-Resolution Remote Sensing Images of Rare Earth Mine in Ganzhou

作　　者：袁秀华[1] 罗卫[1] 王聪颖[1] 

机构地区：[1]江西理工大学,江西赣州341000

出　　处：《测绘与空间地理信息》2013年第9期48-50,共3页Geomatics & Spatial Information Technology

基　　金：国家自然科学基金项目(41101322);江西省自然科学基金项目(20114BAB213022)资助

摘　　要：随着高分辨率遥感影像在矿山分类工作中的广泛应用,面向对象的多尺度分割技术成为研究热点。最优尺度的选取是此类技术的关键。为获取高分遥感影像最适宜的分割尺度,本文以赣州稀土矿山高分辨率遥感影像为源数据,选择与邻域绝对均值差分方差比方法 RMAS(Ratio of Mean Difference to Neighbors(ABS)to Standard Deviation)方法获取最优分割尺度。通过分割质量值对分割结果进行评价分析,研究验证了RMAS方法的可行性。Sincehigh resolution remote sensing image is widely used in the work of mining classification, the technologies of object - oriented multi - scale segmentation become a hot topic. The selection of the optimal scale is the key to such technology. In order to obtain the optimal segmentation scale for high resolution sensing image, high - resolution remote sensing images of Ganzhou rare earth mines are selected as source data and RMAS （Ratio of Mean Difference to Neighbors （ABS） to Standard Deviation） method to obtain the optimal scale in the paper. Segmentation results are evaluated by segmentation quality value, and the study proves the feasibility of RMAS method.

关 键 词：高分辨率遥感影像 多尺度分割 最优尺度 评价分析 

分 类 号：P237[天文地球—摄影测量与遥感] TP75[天文地球—测绘科学与技术]