首页 | 本学科首页   官方微博 | 高级检索  
     检索      

SAR立体影像匹配的视差图融合方法
引用本文:王亚超,张继贤,黄国满,卢丽君,丁昊.SAR立体影像匹配的视差图融合方法[J].测绘学报,2016,45(7):818-824.
作者姓名:王亚超  张继贤  黄国满  卢丽君  丁昊
作者单位:1. 中国矿业大学环境与测绘学院, 江苏 徐州 221008;2. 中国测绘科学研究院, 北京 100830;3. 中南大学地球科学与信息物理学院, 湖南 长沙 410083
基金项目:测绘地理信息公益性行业科研专项(201412002),国家自然科学基金(41401530),对地观测技术国家测绘地理信息局重点实验室基金项目(K201501)
摘    要:提出了一种基于视差图融合的匹配方法。首先,基于归一化互相关系数(normalized cross correlation,NCC),利用多个不同尺寸的匹配窗口分别进行匹配,获取相应的视差图;然后,提出了一种左右一致性(left right consistency,LRC)和信噪比(signal to noise ratio,SNR)相结合的置信测度,用来评价视差图中每个视差的置信水平;在此基础上,提出了一种视差图融合策略,该策略对上述多个匹配窗口获取的视差图进行加权融合,融合时既考虑了视差本身的置信水平,也兼顾了其邻域视差的影响。采用TanDEM-X的聚束立体影像进行试验,结果表明,本文方法能有效减少DEM粗差点,DEM高程精度由11.28 m提高到8.41 m。

关 键 词:归一化互相关系数  视差图融合  置信测度  雷达摄影测量  
收稿时间:2016-01-27
修稿时间:2016-05-02

A StereoSAR Matching Method Based on Disparity Maps Fusion
WANG Yachao,ZHANG Jixian,HUANG Guoman,LU Lijun,DING Hao.A StereoSAR Matching Method Based on Disparity Maps Fusion[J].Acta Geodaetica et Cartographica Sinica,2016,45(7):818-824.
Authors:WANG Yachao  ZHANG Jixian  HUANG Guoman  LU Lijun  DING Hao
Institution:1. School of Environmental Science and Spatial Informatics, China University of Mining and Technology, Xuzhou 221008, China;2. China Academy of Surveying and Mapping, Beijing 100830, China;3. School of Geosciences and Info-Physics, Central South University, Changsha 410083, China
Abstract:A matching algorithm based on disparity maps fusion is proposed.Firstly,on the basis of normalized cross correlation(NCC),various disparity maps are computed using several different matching window sizes.Then,for each disparity of each disparity maps,the confidence level is evaluated by a new confidence measure,which combined left right consistency(LRC)with signal to noise ratio(SNR).Finally,a new proposed disparity maps fusion strategy is used for formation of weighted disparity map in terms of confidence level.This disparity maps fusion strategy considers not only the confidence level of the disparity itself but also its neighbors.The algorithm has been applied to a pair of TanDEM-X spotlight stereo images. The results demonstrate that the accuracy of DEM generated with the proposed algorithm is improved from 11.28 m to 8.41 m and the gross errors are effectively reduced.
Keywords:normalized cross correlation(NCC)  disparity maps fusion  confidence measure  radargrammetry
本文献已被 CNKI 万方数据 等数据库收录!
点击此处可从《测绘学报》浏览原始摘要信息
点击此处可从《测绘学报》下载免费的PDF全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号