Automated Image-Based Abstraction of Aerial Images
Aerial images represent a fundamental type of geodata with a broad range of applications in GIS and geovisualization. The perception and cognitive processing of aerial images by the human, however, still is faced with the specific limitations of photorealistic depictions such as low contrast areas, unsharp object borders as well as visual noise.
In this paper we present a novel technique to automatically abstract aerial images that enhances visual clarity and generalizes the contents of aerial images to improve their perception and recognition. The technique applies non-photorealistic image processing by smoothing local image regions with low contrast and emphasizing edges in image regions with high contrast. To handle the abstraction of large images, we introduce an image tiling procedure that is optimized for post-processing images on GPUs and avoids visible artifacts across junctions. This is technically achieved by filtering additional connection tiles that overlap the main tiles of the input image. The technique also allows the generation of different levels of abstraction for aerial images by computing a mipmap pyramid, where each of the mipmap levels is filtered with adapted abstraction parameters. These mipmaps can then be used to perform level-of-detail rendering of abstracted aerial images.
Finally, the paper contributes a study to aerial image abstraction by analyzing the results of the abstraction process on distinctive visible elements in common aerial image types. In particular, we have identified a high abstraction potential in landscape images and a higher benefit from edge enhancement in urban environments.
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- Bigün, J. and Granlund, G. H. (1987) Optimal orientation detection of linear symmetry, Proceedings of the IEEE First International Conference on Computer Vision, London, Great Britain, pp. 433-438.Google Scholar
- Blom Pictometry (2009) http://www.blompictometry.com, Last date accessed 11.2009.
- Buchholz, H., Döllner, J., Nienhaus, M. and Kirsch, F. (2005) Real-Time Non- Photorealistic Rendering of 3D City Models, 1st International Workshop on Next Generation 3D City Models, EuroSDR.Google Scholar
- Curtis, C. J., Anderson, S. E., Seims J. E., Fleischer, K. W. and Salesin, D. H. (1997) Computer-generated watercolor, SIGGRAPH ’97: Proceedings of the 24th annual conference on Computer graphics and interactive techniques, New York, pp. 421-430.Google Scholar
- Döllner, J. (2007) In: Non-Photorealistic 3D Geovisualization, Multimedia Cartography, Springer, pp. 229-240.Google Scholar
- Döllner, J., Baumann, K., Hinrichs, K. (2000) Texturing techniques for terrain visualization. In: Proceedings of IEEE Visualization, pp. 227-234.Google Scholar
- Döllner, J., Buchholz, H., Nienhaus, M. and Kirsch, F. (2005) Illustrative Visualization of 3D City Models, In: Visualization and Data Analysis, Proceedings of the SPIE, International Society for Optical Engine (SPIE), pp. 42-51.Google Scholar
- Glander, T. and Döllner, J. (2009) Abstract representations for interactive visualization of virtual 3D city models, In: Computers, Environment and Urban SystemsGoogle Scholar
- Gooch, B. and Gooch, A. A. (2001) Non-Photorealistic Rendering, AK Peters Ltd.Google Scholar
- Idbraim, S., Mammass, D., Aboutajdine and Ducrot, D. (2008), An automatic system for urban road extraction from satellite and aerial images, In: WSEAS Trans., Sig. Proceedings, vol. 4, no. 10, pp. 563-572.Google Scholar
- Kuwahara, M., Hachimura, K, Eiho, S. and Kinoshita, M. (1976) Digital processing of biomedical images, Plenum Press.Google Scholar
- Kyprianidis, J. E. and Döllner, J. (2008) Image Abstraction by Structure Adaptive Filtering, In: EG UK Theory and Practice of Computer Graphics, Eurographics Association, pp. 51-58.Google Scholar
- Kyprianidis, J. E., Kang, H. and Döllner, J. (2009) Image and Video Abstraction by Anisotropic Kuwahara Filtering, Computer Graphics Forum, vol. 28, no. 7.Google Scholar
- Leberl, F., Bischof, H., Grabner, H. and Kluckner, S. (2007) Recognizing cars in aerial imagery to improve orthophotos, In: GIS ’07: Proceedings of the 15th annual ACM international symposium on Advances in geographic information systems, New York, pp. 1-9.Google Scholar
- Marr, D. and Hildreth, E. (1980) Theory of edge detection, RoyalP, vol. B-207, pp. 187-217.Google Scholar
- Meng, L. (2002) How can 3D Geovisualization Please Users Eyes Better?, Geoinformatics Magazine for Geo-IT Professionals, Emmeloord, The Netherlands, vol. 5, pp. 34-35Google Scholar
- Muhar, A. (1999) Three-dimensional modeling and visualization of vegetation for landscape simulation, Institute for Landscape Architecture and Landscape Management, Ascona, Switzerland, Technical report.Google Scholar
- Nienhaus, M. (2006) Real-Time Non-Photorealistic Rendering Techniques for Illustrating 3D Scenes and their Dynamics, Ph.D. dissertation, HPI, Universität Potsdam, Germany, 2006.Google Scholar
- NVIDIA Texture Tools 2 - GPU-accelerated Texture Tools with support for DirectX 10 texture formats (2009) http://code.google.com/p/nvidia-texture-tools, Last date accessed 11.2009.
- Paris, S., Kornprobst, P., Tumblin, J. and Durand, F. (2007) A gentle introduction to bilateral filtering and its applications, In: SIGGRAPH ’07: ACM SIGGPRAPH 2007 courses, New York, p. 1.Google Scholar
- Pictometry - The Aerial Oblique Photography Company (2009) http://www.pictometry.com, Last date accessed 11.2009.
- Ram, T. Z., Zhao, T. and Nevatia, R. (2001) Car detection in low resolution aerial images, In: Image and Vision Computing, pp. 710-717.Google Scholar
- Santella, A. (2005) The Art of Seeing: Visual Perception in Design and Evaluation of Non-Photorealistic Rendering, Ph.D. dissertation, Rutgers University, New Brunswick, New Jersey, USA.Google Scholar
- Santella, A. and DeCarlo, D. (2004) Visual interest and NPR: An evaluation and manifesto, In: NPAR ’04: Proceedings of the 3rd international symposium on Non-Photorealistic animation and rendering, New York, USA, pp. 71-150.Google Scholar
- Tanner, C. C., Migdal C. J. and Jones, M. T. (1998) The clipmap: A virtual mipmap, In: SIGGPRAPH ’98: Proceedings of the 25th annual conference on Computer graphics and interactive techniques, New York, USA, pp. 151-158.Google Scholar
- Tomasi, C. and Manduchi, R. (1998) Bilateral filtering for gray and color images, IEEE International Conference on Computer Vision (ICCV), p. 839.Google Scholar
- Williams, L. (1983) Pyramidal parametrics, In: SIGGRAPH ’83: Proceedings of the 10th annual conference on Computer graphics and interactive techniques, New York, pp. 1-11.Google Scholar
- Zhao, F., Zhang, H., Li, Z. and Pang, Y. (2008) The extraction of individual treecrown in aerial digital camera imagery, In: FSKD (3), pp. 183-188.Google Scholar