Small object recognition techniques based on structured template matching for high-resolution satellite images

We are developing infrastructure tools of wide-area monitoring used for such as disaster damaged areas or traffic conditions, using Earth observation satellite images. Especially, we are focusing on developing a small object recognition tool for satellite images, which enables extract automobile patterns in high-resolution satellite images such as QuickBird panchromatic images, for example. Although, resolution of optical sensors installed in the current earth observation satellites has been highly advanced, their pixel resolution is not enough for identifying each small object such as an automobile by the currently available pattern matching techniques. Whereas, the pattern matching calculation load of high-resolution images becomes bigger, it will take tremendous time for searching whole objects included in a slice of satellite images. In order to overcome these problems, we propose a structured template matching technique for recognizing small objects in satellite images, which consists of a micro-template matching, clustered micro-template matching and macro-template matching. In this paper, we describe an abstract of our proposed method and present its experimental results.

[1]  Ramakant Nevatia,et al.  Car Detection in Low Resolution Aerial Image , 2001, ICCV.

[2]  Byung-Doo Kwon,et al.  Application of template matching method to traffic feature detection using KOMPSAT EOC imagery , 2005, Proceedings. 2005 IEEE International Geoscience and Remote Sensing Symposium, 2005. IGARSS '05..

[3]  Ramakant Nevatia,et al.  Car detection in low resolution aerial image , 2001, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001.

[4]  Wang Chao,et al.  Structure-context based fuzzy neural network approach for automatic target detection , 2003, IGARSS 2003. 2003 IEEE International Geoscience and Remote Sensing Symposium. Proceedings (IEEE Cat. No.03CH37477).

[5]  Lin Wang,et al.  The building recognition of high resolution satellite remote sensing image based on wavelet analysis , 2005, 2005 International Conference on Machine Learning and Cybernetics.

[6]  Josiane Zerubia,et al.  Supervised segmentation of remote sensing images based on a tree-structured MRF model , 2005, IEEE Transactions on Geoscience and Remote Sensing.