Full Text:   <3352>

Summary:  <2173>

CLC number: TV149.2

On-line Access: 2014-01-03

Received: 2013-09-24

Revision Accepted: 2013-12-03

Crosschecked: 2013-12-20

Cited: 1

Clicked: 6857

Citations:  Bibtex RefMan EndNote GB/T7714

-   Go to

Article info.
Open peer comments

Journal of Zhejiang University SCIENCE A 2014 Vol.15 No.1 P.68-82

http://doi.org/10.1631/jzus.A1300317


A three-dimensional topographic survey based on two-dimensional image information*


Author(s):  Xiao-long Song1, Yu-chuan Bai1,2, Chao Ying3

Affiliation(s):  1. State Key Laboratory of Hydraulic Engineering Simulation and Safety, Tianjin University, Tianjin 300072, China; more

Corresponding email(s):   sxlong2013@foxmail.com

Key Words:  Riverbed topographic survey, Radial distortion calibration, Projection transformation, Grey information transformation


Share this article to: More <<< Previous Article|

Xiao-long Song, Yu-chuan Bai, Chao Ying. A three-dimensional topographic survey based on two-dimensional image information[J]. Journal of Zhejiang University Science A, 2014, 15(1): 68-82.

@article{title="A three-dimensional topographic survey based on two-dimensional image information",
author="Xiao-long Song, Yu-chuan Bai, Chao Ying",
journal="Journal of Zhejiang University Science A",
volume="15",
number="1",
pages="68-82",
year="2014",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.A1300317"
}

%0 Journal Article
%T A three-dimensional topographic survey based on two-dimensional image information
%A Xiao-long Song
%A Yu-chuan Bai
%A Chao Ying
%J Journal of Zhejiang University SCIENCE A
%V 15
%N 1
%P 68-82
%@ 1673-565X
%D 2014
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.A1300317

TY - JOUR
T1 - A three-dimensional topographic survey based on two-dimensional image information
A1 - Xiao-long Song
A1 - Yu-chuan Bai
A1 - Chao Ying
J0 - Journal of Zhejiang University Science A
VL - 15
IS - 1
SP - 68
EP - 82
%@ 1673-565X
Y1 - 2014
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.A1300317


Abstract: 
A riverbed topographic survey is one of the most important tasks for river model experiments. To improve measurement efficiency and solve the riverbed interference problem in traditional methods, this study discussed two measurement methods that use digital image-processing technology to obtain topographic information. A new and improved approach for calibrating camera radial distortion, which comes from originally distorted images captured by our camera, was proposed to enhance the accuracy of image measurement. Based on perspective projection transformation, we described a 3D reconstruction method based upon multiple images, which is characterized by using an approximated maximum likelihood estimation method (AMLE) considering the first-order error propagation of the residual error to compute transformation parameters. Moreover, a theoretical derivation of 3D topography according to grey information from a single image was carried out. With the diffuse illumination model, assuming that the ideal grey value and topographic elevation value are positively correlated, we derived a novel closed formula to explain the relationship of 3D topographic elevation, grey value, grey gradient, and the solar direction vector. Experimental results showed that our two methods both have some positive advantages even if they are not perfect.

一种基于二维图像信息的三维地形测量

研究目的:利用数字图像测量技术对河流模型实验中的河床地形测量研究。
创新方法:以高质量的图像径向畸变校正为基础,依据多幅图像间映射换算以及单幅图像灰度信息变换两方面的研究,来提取三维地形信息。
研究手段:使用考虑残差的一阶误差传播的最大似然估计方法求解图像与地形坐标的映射变换参数;借助漫反射光照模型,通过适当假设,推导出地形高程与图像灰度、灰度梯度及太阳方向的关系式。
重要结论:1.以Devernay基于直线的图像畸变校正方法为基础,通过使用更高精度的Canny边缘检测算子提取图像边缘,黄金分割法和二次插值法相结合的最优化方法求取畸变系数等,可以得到较好的校正效果,求算的畸变系数精度更高,求算过程更快;2.利用图像与地面间的透视投影关系方法求解地形高程坐标,均匀并尽可能多地将控制点布置在控制区域内,使计算值更接近实测值,并满足河流演变实验的精度要求;3.通过推导关系式,理论上可以根据图像灰度、灰度梯度、太阳方向向量算得地形高程。

关键词:河床地形测量;数字图像测量技术;径向畸变矫正;投影变换;灰度信息变换

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

References

[1] Ahmed, M., Farag, A., 2005. Nonmetric calibration of camera lens distortion: differential methods and robust estimation. IEEE Transactions on Image Processing, 14(8):1215-1230. 


[2] Alho, P., Kukko, A., Hyypp, H., 2009. Application of boat-based laser scanning for river survey. Earth Surface Processes and Landforms, 34(13):1831-1838. 


[3] Astruc, D., Cazin, S., Cid, E., 2012. A stereoscopic method for rapid monitoring of the spatio-temporal evolution of the sand-bed elevation in the swash zone. Coastal Engineering, 60:11-20. 


[4] Benetazzo, A., 2006. Measurements of short water waves using stereo matched image sequences. Coastal Engineering, 53(12):1013-1032. 


[5] Bouratsis, P., Diplas, P., Dancey, C.L., 2013. High-resolution 3-D monitoring of evolving sediment beds. Water Resources Research, 49(2):977-992. 


[6] Brasington, J., 2010. From grain to floodplain: hyperscale models of braided rivers. Journal of Hydraulic Research, 48(4):52-53. 

[7] Butler, J.B., Lane, S.N., Chandler, J.H., 2001. Characterization of the structure of river-bed gravels using two-dimensional fractal analysis. Mathematical Geology, 33(3):301-330. 


[8] Chandler, J., Ashmore, P., Paola, C., 2002. Monitoring river-channel change using terrestrial oblique digital imagery and automated digital photogrammetry. Annals of the Association of American Geographers, 92(4):631-644. 


[9] Chen, L., Armstrong, C.W., Raftopoulos, D.D., 1994. An investigation on the accuracy of three-dimensional space reconstruction using the direct linear transformation technique. Journal of Biomechanics, 27(4):493-500. 


[10] Chojnacki, W., Brooks, M.J., van den Hengel, A., 2000. On the fitting of surfaces to data with covariances. IEEE Transactions on Pattern Analysis and Machine Intelligence, 22(11):1294-1303. 


[11] Devernay, F., Faugeras, O., 1995. Automatic calibration and removal of distortion from scenes of structured environments. , Investigative and Trial Image Proceedings, San Diego, CA, USA, 62-72. :62-72. 


[12] Devernay, F., Faugeras, O., 2001. Straight lines have to be straight. Machine Vision and Applications, 13(1):14-24. 


[13] Feng, S.J., Chen, Q., Zuo, C., 2013. Automatic identification and removal of outliers for high-speed fringe projection profilometry. Optical Engineering, 52(1):013605


[14] Fonstad, M.A., Dietrich, J.T., Courville, B.C., 2013. Topographic structure from motion: a new development in photogrammetric measurement. Earth Surface Processes and Landforms, 38(4):421-430. 


[15] Forsyth, D.A., Ponce, J., 2002.  Computer Vision: a Modern Approach. Prentice Hall, Inc.,New Jersey, USA :

[16] Gallego, G., Yezzi, A., Fedele, F., 2011. A variational stereo method for the three-dimensional reconstruction of ocean waves. IEEE Transactions on Geoscience and Remote Sensing, 49(11):4445-4457. 


[17] Gomez, A., Pushparajah, K., Simpson, J.M., 2013. A sensitivity analysis on 3D velocity reconstruction from multiple registered echo Doppler views. Medical Image Analysis, 17(6):616-631. 


[18] Gong, C., Wang, Z.L., 2009.  Proficient in Matlab Optimization Calculation. (in Chinese), Publishing House of Electronics Industry,Beijing, China :

[19] He, J., Wang, X.S., Li, Q.H., 2008. Optics imaging model based on DEM. Computer Engineering, (in Chinese),34(1):50-52. 

[20] Heritage, G., Hetherington, D., 2007. Towards a protocol for laser scanning in fluvial geomorphology. Earth Surface Processes and Landforms, 32(1):66-74. 


[21] Hfle, B., Rutzinger, M., 2011. Topographic airborne LiDAR in geomorphology: a technological perspective. Zeitschrift fr Geomorphologie, Supplementary Issues, 55(2):1-29. 


[22] Hohenthal, J., Alho, P., Hyypp, J., 2011. Laser scanning applications in fluvial studies. Progress in Physical Geography, 35(6):782-809. 


[23] James, M.R., Robson, S., 2012. Straightforward reconstruction of 3D surfaces and topography with a camera: accuracy and geoscience application. Journal of Geophysical Research: Earth Surface, 117:F03017


[24] Jiang, D.Z., Yu, Q., Wang, B.Y., 2001. Research and overview of imaging nonlinear distortion in computer vision. Computer Engineering, (in Chinese),27(12):108-110. 

[25] Kanatani, K., 1996.  Statistical Optimization for Geometric Computation: Theory and Practice. Elsevier Science,Amsterdam :

[26] Li, J., 1991.  Computer Vision Theory and Practice. (in Chinese), Shanghai Jiao Tong University Press,Shanghai, China :

[27] Lohry, W., Zhang, S., 2012. Fourier transform profilometry using a binary area modulation technique. Optical Engineering, 51(11):113602


[28] Lu, S.L., Shen, X.H., Zou, L.J., 2008. An integrated classification method for thematic mapper imagery of plain and highland terrains. Journal of Zhejiang University-SCIENCE A, 9(6):858-866. 


[29] Matei, B., Meer, P., 2000. A general method for errors-in-variables problems in computer vision. , Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 18-25. :18-25. 


[30] Miks, A., Novak, J., 2012. Dependence of camera lens induced radial distortion and circle of confusion on object position. Optics & Laser Technology, 44(4):1043-1049. 


[31] Miks, A., Novak, J., Novak, P., 2013. Method for reconstruction of shape of specular surfaces using scanning beam deflectometry. Optics and Lasers in Engineering, 51(7):867-872. 


[32] Mohammed, T.S., Al-Azzo, W.F., Al Mashani, K.M., 2013. Image processing development and implementation: a software simulation using Matlab®. , Proceedings of the 6th International Conference on Information Technology, :

[33] Muhlich, M., Mester, R., 2001. Subspace methods and equilibration in computer vision. , Proceedings of the Scandinavian Conference on Image Analysis, Bergen, Norway, 415-422. :415-422. 

[34] Notebaert, B., Verstraeten, G., Govers, G., 2009. Qualitative and quantitative applications of LiDAR imagery in fluvial geomorphology. Earth Surface Processes and Landforms, 34(2):217-231. 


[35] Omar, K., Ramli, A.R., Mahmod, R., 2012. Skew detection and correction of Jawi images using gradient direction. Jurnal Teknologi, 37:117-126. 


[36] Per, J., Kovacic, S., 2002. Nonparametric, model-based radial lens distortion correction using tilted camera assumption. , Proceedings of the Computer Vision Winter Workshop, Bad Aussee, Austria, 286-295. :286-295. 

[37] Pollefeys, M., Gool, L.V., 2002. From images to 3D models. Communications of the ACM, 45(7):50-55. 


[38] Shashua, A., 1997. On photometric issues in 3D visual recognition from a single 2D image. International Journal of Computer Vision, 21(1-2):99-122. 


[39] Tordoff, B., Murray, D.W., 2000. Violating rotating camera geometry: the effect of radial distortion on self-calibration. , Proceedings of the 15th IEEE International Conference on Pattern Recognition, Barcelona, Spain, 423-427. :423-427. 


[40] Wang, B., Tang, J., 2001. Comparison of the different methods for solor position calculation. Acta Energiae Solaris Sinica, (in Chinese),22(4):413-417. 

[41] Wang, J.H., Shi, F.H., Zhang, J., 2008. A new calibration model of camera lens distortion. Pattern Recognition, 41(2):607-615. 


[42] Wang, Z., 2007.  Photogrammetry Principle. (in Chinese), Wuhan University Press,Wuhan, China :

[43] Weng, J., Cohen, P., Herniou, M., 1992. Camera calibration with distortion models and accuracy evaluation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 14(10):965-980. 


[44] Xu, D., Bai, Y.C., 2013. Experimental study on the bed topography evolution in alluvial meandering rivers with various sinuousnesses. Journal of Hydro-environment Research, 7(2):92-102. 


[45] Yoo, H., 2013. Depth extraction for 3D objects via windowing technique in computational integral imaging with a lenslet array. Optics and Lasers in Engineering, 51(7):912-915. 


[46] Yu, W., Zhou, S., Wang, W., 2003.  The Ground Meteorological Observation Specification. (in Chinese), China Meteorological Press,Beijing, China :

[47] Yu, Z., Ce, H., Yu, Z., 1990.  Measuring Adjustment Principle. (in Chinese), Wuhan Technical University of Surveying and Mapping Press,Wuhan, China :

[48] Zhang, C., Lv, D.H., Xu, C.J., 2010. Computation for solar real-time position and its application in illuminant direction of image. Electronic Measurement Technology, (in Chinese),33(11):87-93. 

[49] Zhang, R., Tsai, P.S., Cryer, J.E., 1999. Shape-from-shading: a survey. IEEE Transactions on Pattern Analysis and Machine Intelligence, 21(8):690-706. 


[50] Zhang, Y.J., 2000.  Image Understanding and Computer Vision. (in Chinese), Tsinghua University Press,Beijing, China :

[51] Zhang, Z.Y., 2000. A flexible new technique for camera calibration. IEEE Transactions on Pattern Analysis and Machine Intelligence, 22(11):1330-1334. 


[52] Zhou, Y., Deng, C., 2011. Approximated maximum likelihood estimation approach for direct linear transformation. Geotechnical Investigation & Surveying, (in Chinese),39(12):50-54. 

[53] Zhu, S.H., Hu, H.B., 2012. Analysis of the effect on optical equipment caused by solar position in target flight measure. , Proceedings of SPIE, Optoelectronic Imaging and Multimedia Technology II, 85581V, :


[54] Zwick, S., Heist, S., Franzl, Y., 2013. Wide-band phase-shifting fringe projector on the basis of a tailored free-form mirror. Optical Engineering, 52(2):023001



Open peer comments: Debate/Discuss/Question/Opinion

<1>

Please provide your name, email address and a comment





Journal of Zhejiang University-SCIENCE, 38 Zheda Road, Hangzhou 310027, China
Tel: +86-571-87952783; E-mail: cjzhang@zju.edu.cn
Copyright © 2000 - 2024 Journal of Zhejiang University-SCIENCE