Chenglin Bian
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Chenglin Bian has a total of 5 co-authors. Here are the top co-authors by number of shared publications:
- Haizhong Qian
Institute of Geospatial Information, Information Engineering University, Zhengzhou 450001, China
1 shared publication - Limin Xie
Institute of Geospatial Information, Information Engineering University, Zhengzhou 450001, China
1 shared publication - Linghui Kong
Institute of Geospatial Information, Information Engineering University, Zhengzhou 450001, China
1 shared publication - Yue Qiu
Institute of Geospatial Information, Information Engineering University, Zhengzhou, China
1 shared publication - Zhekun Huang
Institute of Geospatial Information, Information Engineering University, Zhengzhou 450001, China
1 shared publication
Latest Publications
- Open Access
- 22 November 2023
- Published by MDPI AG in Applied Sciences
- Vol. 13 (23) , 12599
Multilevel Regularization Method for Building Outlines Extracted from High-Resolution Remote Sensing Images
Extraction of vectorized building outlines from high-resolution remote sensing images is highly useful for various application fields, such as map creation and urban planning. However, this process is often complicated by external factors, such as trees and shadows, which cause issues, such as excessive node redundancy, jagged lines, and unclear corner points. In this study, a multilevel regularization method was designed for building outlines, including the “overall–local–detail” levels. First, overall regularization was performed by combining the minimum bounding rectangle of the building outline with the Hausdorff distance method. Next, based on the convex hull of the building outline and the distribution characteristics of nodes along the outline, the building outline was divided into multiple line chains and classified for local regularization. Finally, the details of the building outline were processed, with the parallel and perpendicular characteristics enhanced to obtain the final regularization results. The experimental results showed that the proposed method effectively enhances the edge representation accuracy of building outlines and significantly improves the accuracy and regularity of building edges. Furthermore, it strengthens the orthogonal characteristics of building outlines, providing more accurate representations of true building outlines.
- 22 November 2023
- Published by MDPI AG in Applied Sciences
- Vol. 13 (23) , 12599
Open AccessMultilevel Regularization Method for Building Outlines Extracted from High-Resolution Remote Sensing Images
Extraction of vectorized building outlines from high-resolution remote sensing images is highly useful for various application fields, such as map creation and urban planning. However, this process is often complicated by external factors, such as trees and shadows, which cause issues, such as excessive node redundancy, jagged lines, and unclear corner points. In this study, a multilevel regularization method was designed for building outlines, including the “overall–local–detail” levels. First, overall regularization was performed by combining the minimum bounding rectangle of the building outline with the Hausdorff distance method. Next, based on the convex hull of the building outline and the distribution characteristics of nodes along the outline, the building outline was divided into multiple line chains and classified for local regularization. Finally, the details of the building outline were processed, with the parallel and perpendicular characteristics enhanced to obtain the final regularization results. The experimental results showed that the proposed method effectively enhances the edge representation accuracy of building outlines and significantly improves the accuracy and regularity of building edges. Furthermore, it strengthens the orthogonal characteristics of building outlines, providing more accurate representations of true building outlines.