摘要
多源、多时相与多尺度DEM的匹配是DEM(Digital Elevation Model)应用中的关键技术。对无空间参考的DEM进行匹配时,若特征点不足或匹配DEM之间的分辨率、地形特征等差异较大,已有的DEM匹配技术往往难以成功。为此,这里提出了基于矩形特征的模糊匹配方法。首先利用矩形特征构建了五种图像相似度指标BRFSI并统计分析了各个指标的分类性能;然后,使用Gentle AdaBoost算法对大量样本进行训练后,得到了用于判定"匹配"与"非匹配"的分类器;最后建立了进行DEM图像模糊匹配的匹配模型。经过四种典型数据验证,该方法很好地解决了无空间参考DEM匹配中特征点不足、DEM之间相似度较低的难点问题,为进一步的DEM精匹配提供了良好的初始条件。
One of the key technologies of DEM application is multi-source,multi-temporal and multi-scale DEM matching.The existing DEM matching technologies usually fail when DEM is matched without spatial reference because of the insufficient feature points or the vast differences of resolution,terrain features and some others.Therefore,the method,fuzzy matching of DEM without spatial reference based on rectangle features,is proposed in this paper.First,five images similarity indicators were constructed based on rectangle features and then the statistical analysis was used respectively in every indicator's classification performance.Second,the classifier,to discriminate whether matched or not,was obtained after using Gentle AdaBoost algorithm training massive samples.Finally,a model of DEM image fuzzy matching was established.The method used in this paper shows a capability in solving two difficult problems,the lack of feature points when DEM is matched without spatial reference and low similarity between DEM data,by verifying of four typical data.All these above may provide precise DEM matching a fine initial condition.
出处
《物探化探计算技术》
CAS
CSCD
2016年第2期264-274,共11页
Computing Techniques For Geophysical and Geochemical Exploration
基金
国家自然科学基金资助项目(批准号:41372340)
国土资源部地学空间信息技术重点实验室开放基金资助项目(KLGSIT2014-05)