References
- Avbelj, J., D. Iwaszczuk, R. Müller, P. Reinartz, and U. Stilla. 2015. “Co-Registration Refinement of Hyperspectral Images and DSM: An Object-Based Approach Using Spectral Information.Isprs.” ISPRS Journal of Photogrammetry and Remote Sensing 100: 23–34. doi:10.1016/j.isprsjprs.2014.05.010.
- Biswas, P., A. Paul, and P. Bhattacharya. 2015. “Generating Spanning Tree of Non-Regular Graphic Sequences through a Variant of Prim’s Algorithm. International Conference on Circuit.” Power and Computing Technologies (ICCPCT) 1 (4): 19–20.
- Blaschke, T. 2010. “Object Based Image Analysis for Remote Sensing.” ISPRS Journal of Photogrammetry and Remote Sensing 65 (1): 2–16. doi:10.1016/j.isprsjprs.2009.06.004.
- Brook, A., E. Ben-Dor, and R. Richter. 2010. “Fusion of Hyperspectral Images and Lidar Data for Civil Engineering Structure Monitoring.” 2nd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, Reykjavik, June 14–16, 1–5.
- Ceresola, S., A. Fusiello, M. Bicego, A. Belussi, and V. Murino. 2005. “Automatic Updating of Urban Vector Maps.” In Image Analysis and Processing – ICIAP 2005, edited by F. Roli and S. Vitulano, 1133–1139. Berlin: Springer-Verlag.
- Champion, N. 2007. “2D Building Change Detection from High-Resolution Aerial Images and Correlation Digital Surface Models.” International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences 36 (3): 197–202.
- Comaniciu, D., and P. Meer. 2002. “Mean Shift: A Robust Approach toward Feature Space Analysis.” IEEE Transactions on Pattern Analysis and Machine Intelligence 24 (5): 603–619. doi:10.1109/34.1000236.
- Durieux, L., E. Lagabrielle, and A. Nelson. 2008. “A Method for Monitoring Building Construction in Urban Sprawl Areas Using Object-Based Analysis of Spot 5 Images and Existing GIS Data.” ISPRS Journal of Photogrammetry and Remote Sensing 63 (4): 399–408. doi:10.1016/j.isprsjprs.2008.01.005.
- Goodchild, M. F. 2007. “Citizens as Sensors: The World of Volunteered Geography.” GeoJournal 69 (4): 211–221. doi:10.1007/s10708-007-9111-y.
- Growe, S., and R. Tonjes. 1997. “A Knowledge-Based Approach to Automatic Image Registration.” Proceedings of the IEEE International Conference on Image Processing ICIP’97, Santa Barbara, CA, October 26–29, 228–231.
- Guo, Z., S. Du, M. Li, and W. Zhao. 2016. “Exploring GIS Knowledge to Improve Building Extraction and Change Detection from VHR Imagery in Urban Areas.” International Journal of Image and Data fusion 7 (1): 42–62. doi:10.1080/19479832.2015.1051138.
- Habbecke, M., and L. Kobbelt. 2010. “Automatic Registration of Oblique Aerial Images with Cadastral Maps.” ECCV Workshop on Reconstruction and Modeling of Large-Scale 3D Virtual Environments 6554 (1): 253–266.
- Habib, A., Y. Lee, and M. Morgan. 2003. “Automatic Matching and Three-Dimensional Reconstruction of Free-Form Linear Features from Stereo Images.” Photogrammetric Engineering & Remote Sensing 69 (2): 189–197. doi:10.14358/PERS.69.2.189.
- Henricsson, O. 1998. “The Role of Color Attributes and Similarity Grouping in 3-D Building Reconstruction.” Computer Vision and Image Understanding 72 (2): 163–184. doi:10.1006/cviu.1998.0718.
- Ion, A., W. G. Kropatsch, and Y. Haxhimusa. 2006. Considerations regarding the Minimum Spanning Tree Pyramid Segmentation Method, 182–191. Berlin: Springer.
- Sebari, I., and D. He. 2013. “Automatic Fuzzy Object-Based Analysis of VHSR Images for Urban Objects Extraction.” ISPRS Journal of Photogrammetry and Remote Sensing 79: 171–184. doi:10.1016/j.isprsjprs.2013.02.006.
- Vasileisky, A., B. Zhukov, and M. Berger. 1998. “Automated Image Co-Registration Based on Linear Feature Recognition.” Proceedings of the Second Conference Fusion of Earth Data, Sophia Antipolis, January 28–30, 59–66. SEE/URISCA, France.
- Zhang, L., 2005. Automatic digital surface model (DSM) generation from linear array images. PhD thesis, Institute of Geodesy and Photogrammetry, Swiss Federal Institute of Technology, Zurich.
- Zitová, B., and J. Flusser. 2003. “Image Registration Methods: A Survey.” Image and Vision Computing 21 (11): 977–1000. doi:10.1016/S0262-8856(03)00137-9.