基于形状先验的建筑物几何参数提取方法

王陈园; 吴斌; 王宏琦

doi:10.11999/JEIT161224

基于形状先验的建筑物几何参数提取方法

doi: 10.11999/JEIT161224

基金项目:

国家自然科学基金(61302170)

计量
- 文章访问数: 1167
- HTML全文浏览量: 109
- PDF下载量: 337
- 被引次数: 0
出版历程
- 收稿日期: 2016-11-14
- 修回日期: 2017-03-27
- 刊出日期: 2017-08-19

Geometric Parameters Extraction of Building Based on Shape Prior

Funds:

The National Natural Science Foundation of China (61302170)

摘要

摘要: 基于单幅高分辨率遥感图像的建筑物几何参数提取结果的准确性，容易受图像背景、图像噪声以及灰度分布相似性的干扰，形成错误的提取结果。针对这一问题，该文提出一种新的基于形状先验的变分水平集提取方法，该方法同时使用图像边缘信息、区域灰度信息以及包含屋顶和侧立面的形状先验信息，实现单幅遥感图像中建筑物的几何参数的提取。实验结果表明，该方法能够更加准确地提取建筑物，最后得到的几何参数比较接近真值，并且由于更加充分地使用了全局形状信息该方法能更好地抵制侧立面的干扰，具有很强的鲁棒性。
- 遥感图像处理 /
- 建筑物几何参数提取 /
- 变分水平集模型 /
- 曲线演化 /
- 形状先验
Abstract: Due to algorithms for buildings geometric parameters extraction from single high remote sensing image usually suffer from disturbances of background, noise and intensity similarity, resulting in wrong extraction results. In this paper, a novel variational level set model is proposed based on shape prior which integrates edge, gray, and shape prior including roof and facade, to extract buildings geometric parameters from a single high resolution remote sensing image. Experimental results show that the proposed method can extract buildings geometric parameters accurately. Moreover, it has strong robustness with respect to the disturbance of facade due to the more sufficient utilization of the whole shape prior.
- Remote sensing image processing /
- Buildings geometric parameters extraction /
- Variational level set /
- Curve evolution /
- Shape prior

HTML全文

参考文献(23)

IRVIN R B and MCKEOWN D M. Methods for exploiting the relationship between buildings and their shadows in aerial imagery[C]. International Society for Optics and Photonics, Los Angeles, USA, 1989: 1564-1575.

CHAUDHURI D, KUSHWAHA N K, SAMAL A, et al. Automatic building detection from high-resolution satellite images based on morphology and internal gray variance[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2016, 9(5): 1767-1779. doi: 10.1109/jstars.2015.2425655.

WANG Jun, YANG Xiucheng, QIN Xuebin, et al. An efficient approach for automatic rectangular building extraction from very high resolution optical satellite imagery[J]. IEEE Geoscience and Remote Sensing Letters, 2015, 12(3): 487-491. doi: 10.1109/LGRS.2014.2347332.

HAN Feng and ZHU Songchun. Automatic single view building reconstruction by integrating segmentation[C]. IEEE Conference on Computer Vision Pattern Recognition, Washington, D.C., USA, 2004: 53-59.

吕东岳, 黄志蓓, 陶冠宏, 等. 使用简易深度成像设备的高尔夫挥杆动态贝叶斯网络三维重建[J]. 电子与信息学报, 2015, 37(9): 2076-2081. doi: 10.11999/JEIT150165.

L Dongyue, HUANG Zhipei, TAO Guanhong, et al. Dynamic bayesian network model based golf swing 3D reconstruction using simple depth imaging device[J]. Journal of Electronics Information Technology, 2015, 37(9): 2076-2081. doi: 10.11999/JEIT150165.

STASSOPOULOU A and CAELLI T. Building detection using bayesian networks[J]. International Journal of Pattern Recognition and Artificial Intelligence, 2000, 14(6): 715-733. doi: 10.1142/s0218001400000477.

YANG Pingl, ZHOU Zeming, HUANG Sixun, et al. Segmentation for remote sensing image with shape and spectrum prior[J]. Neurocomputing, 2016, 216: 746-755. doi: 10.1016/j.neucom.2016.08.035.

KASS M, WITKIN A, and TERZOPOULOS D. Snakes: Active contour models[J]. International Journal of Computer Vision, 1988, 1(4): 321-331. doi: 10.1007/BF00133570.

XU Chenyang and PRINCE J. Gradient vector flow: A new external force for snakes[C]. IEEE Computer Society Conference on Computer Vision Pattern Recognition, San Juan, Puerto Rico, 1997: 66-71.

CASELLES V, CATTE F, COLL T, et al. A geometric model for active contours in image processing[J]. Numerische Mathematik, 1993, 66(1): 1-31. doi: 10.1007/BF01385685.

LI Chunming, XU Chenyang, GUI Changfeng, et al. Distance regularized level set evolution and its application to image segmentation[J]. IEEE Transactions on Image Processing, 2010, 19(12): 3243-3254. doi: 10.1109/TIP.2010.2096950.

CHAN T and VESE L. Active contours without edges[J]. IEEE Transactions on Image Processing, 2001, 10(2): 266-277. doi: 10.1109/83.902291.

MUMFORD D and SHAH J. Optimal approximations by piecewise smooth functions and associated variational problems[J]. Communications on Pure Applied Mathematics, 1989, 42(5): 577-685. doi: 10.1002/cpa. 3160420503.

LEVENTON M, GRIMSON W, and FAUGERAS O. Statistical shape influence in geodesic active contours[C]. IEEE Conference on Computer Vision Pattern Recognition (CVPR), Hilton Head Island, USA, 2000: 316-323.

LI Zhongbin, LIU Zhizhao, and SHI Wenzhong. A fast level set algorithm for building roof recognition from high spatial resolution panchromatic images[J]. IEEE Geoscience and Remote Sensing Letters, 2014, 11(4): 743-747. doi: 10.1109/ LGRS.2013.2278342.

田昊, 杨剑, 汪彦明. 基于先验形状约束水平集模型的建筑物提取方法[J]. 自动化学报, 2010, 36(11): 1502-1511. doi: 10.3724/SP.J.1004.2010.01502.

TIAN Hao, YANG Jian, and WANG Yanming. Towards automatic building extraction: Variational level set model using prior shape knowledge[J]. Journal of Automatica Sinica, 2010, 36(11): 1502-1511. doi: 10.3724/SP.J.1004.2010.01502.

PRISACARIU V A, KAHLER O, MURRAY D W, et al. Real-time 3D tracking and reconstruction on mobile phones[J]. IEEE Transactions on Visualization and Computer Graphics, 2015, 21(5): 557-570. doi: 10.1109/TVCG.2014. 2355207.

PARAGIOS N, ROUSSON M, and RAMESH V. Matching distance function: A shape-to-are variational approach for global-to-local registration[C]. European Conference on Computer Vison (ECCV), Copenhangen, Denmark, 2002: 775-789.

杜平, 徐大为, 刘重庆. 飞机飞行姿态仿真的研究[J]. 红外与激光工程, 2000, 29(5): 1-4. doi: 10.3969/j.issn.1007-2276. 2000.05.001.

DU Ping, XU Dawei, and LIU Chongqing. Research of simulation of aircraft status[J]. Infrared and Laser Engineering, 2000, 29(5): 1-4. doi: 10.3969/j.issn.1007-2276. 2000.05.001.

AUBERT G and KORNPROBST P. Mathematical problems in image processing: partial differential equations and the calculus of variations[J]. Applied Intelligence, 2002, 40(2): 291-304. doi: 10.1007/b97428.

施引文献

资源附件(0)

访问统计