顾及纹理特征的航空影像自适应密集匹配方法

doi:10.11947/j.AGCS.2017.20150608

测绘学报 ›› 2017, Vol. 46 ›› Issue (1): 62-72.doi: 10.11947/j.AGCS.2017.20150608

顾及纹理特征的航空影像自适应密集匹配方法

朱庆^1,2, 陈崇泰^1,5, 胡翰^1,3, 丁雨淋^1,4

1. 西南交通大学地球科学与环境工程学院, 四川成都 611756;
2. 西南交通大学高速铁路运营安全空间信息技术国家地方联合工程实验室, 四川成都 611756;
3. 香港理工大学土地测量与地理资讯学系, 香港 999077;
4. 香港中文大学太空与地球信息科学研究所, 香港 999077;
5. 深圳市数字城市工程研究中心, 广东深圳 518034

收稿日期:2015-12-01 修回日期:2016-12-08 出版日期:2017-01-20 发布日期:2017-02-06
通讯作者: 胡翰 E-mail:huhan19880715@163.com
作者简介:朱庆(1966-),男,博士,教授,博士生导师,研究方向为多维动态GIS与虚拟地理环境。E-mail:zhuq66@263.net
基金资助:
国家自然科学基金（41501421；41631174；61602392）；空间信息智能感知与服务深圳市重点实验室（深圳大学）开放基金；测绘遥感信息工程国家重点实验室（武汉大学）基金（15I01）

An Adaptive Dense Matching Method for Airborne Images Using Texture Information

ZHU Qing^1,2, CHEN Chongtai^1,5, HU Han^1,3, DING Yulin^1,4

1. Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu 611756, China;
2. State-Province Joint Engineering Laboratory of Spatial Information Technology of High-speed Rail Safety, Southwest Jiaotong University, Chengdu 611756, China;
3. Department of Land Surveying and Geo-information, Hong Kong 999077, China;
4. Institute of Space and Earth Information Science, Hong Kong 999077, China;
5. Shenzhen Research Center of Digital City Engineering, Shenzhen 518034, China

Received:2015-12-01 Revised:2016-12-08 Online:2017-01-20 Published:2017-02-06
Supported by:
The National Natural Science Foundation of China (Nos.41501421;41631174;61602392);The Foundation of Key Laboratory for Geo-Environmental Monitoring of Coastal Zone of the National Administration of Surveying, Mapping and Geoinformation;Open Research Fund of State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing (No.15I01)

摘要/Abstract

摘要： 半全局匹配实质是在视差连续性假设下的离散优化方法。为克服视差断裂带影响，依赖一组参数控制视差不一致性。若参数过小，在平面内难以保证视差连续性，产生明显噪声，导致凹凸不平现象；若参数过大，将致使物体表面过于平滑，难以保留视差断裂等重要特征。为克服上述问题，本文提出了一种顾及纹理特征的自适应密集匹配方法：首先，检测影像纹理特征并定量表达纹理丰富性程度；其次，依据纹理丰富程度与视差差异存在正相关的规则知识，实现匹配参数依据纹理信息的自适应选择；最后，采用上述参数进行自适应的半全局匹配。通过ISPRS基准数据集和国产SWDC-5获取的倾斜影像进行试验分析证明，本文方法能够有效减少低纹理区域匹配噪声，同时更有效保留边缘特征。

关键词: 影像密集匹配, 半全局匹配, 纹理特征, 自适应方法

Abstract: Semi-global matching (SGM) is essentially a discrete optimization for the disparity value of each pixel, under the assumption of disparity continuities. SGM overcomes the influence of the disparity discontinuities by a set of parameters. Using smaller parameters, the continuity constraint is weakened, which will cause significant noises in planar and textureless areas, reflected as the fluctuations on the final surface reconstruction. On the other hands, larger parameters will impose too much constraints on continuities, which may lead to losses of sharp features. To address this problem, this paper proposes an adaptive dense stereo matching methods for airborne images using with texture information. Firstly, the texture is quantified, and under the assumption that disparity variation is directly proportional to the texture information, the adaptive parameters are gauged accordingly. Second, SGM is adopted to optimize the discrete disparities using the adaptively tuned parameters. Experimental evaluations using the ISPRS benchmark dataset and images obtained by the SWDC-5 have revealed that the proposed method will significantly improve the visual qualities of the point clouds.

Key words: dense image matching, semi-global matching, texture feature, adaptive method

中图分类号:

P231

朱庆, 陈崇泰, 胡翰, 丁雨淋. 顾及纹理特征的航空影像自适应密集匹配方法[J]. 测绘学报, 2017, 46(1): 62-72.

ZHU Qing, CHEN Chongtai, HU Han, DING Yulin. An Adaptive Dense Matching Method for Airborne Images Using Texture Information[J]. Acta Geodaetica et Cartographica Sinica, 2017, 46(1): 62-72.

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顾及纹理特征的航空影像自适应密集匹配方法

An Adaptive Dense Matching Method for Airborne Images Using Texture Information

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