Detection of compound structures using a Gaussian mixture model with spectral and spatial constraints
Please cite this item using this persistent URLhttp://hdl.handle.net/11693/28244
Proceedings of SPIE - The International Society for Optical Engineering
- Conference Paper 
High spectral and high spatial resolution images acquired from new generation satellites have enabled new applications. However, the increasing amount of detail in these images also necessitates new algorithms for automatic analysis. This paper describes a new approach to discover compound structures such as different types of residential, commercial, and industrial areas that are comprised of spatial arrangements of primitive objects such as buildings, roads, and trees. The proposed approach uses a robust Gaussian mixture model (GMM) where each Gaussian component models the spectral and shape content of a group of pixels corresponding to a primitive object. The algorithm can also incorporate spatial constraints on the layout of the primitive objects in terms of their relative positions. Given example structures of interest, a new learning algorithm fits a GMM to the image data, and this model can be used to detect other similar structures by grouping pixels that have high likelihoods of belonging to the Gaussian object models while satisfying the spatial layout constraints without any requirement for region segmentation. Experiments using WorldView-2 data show that the proposed method can detect high-level structures that cannot be modeled using traditional techniques. © 2012 SPIE.
Showing items related by title, author, creator and subject.
Urfalioglu O.; Thormählen, T.; Broszio H.; Mikulastik P.; Cetin, A.E. (2011)In general, feature points and camera parameters can only be estimated with limited accuracy due to noisy images. In case of collinear feature points, it is possible to benefit from this geometrical regularity by correcting ...
Gürler Ü.; Kvam P. (2011)In most reliability studies involving censoring, one assumes that censoring probabilities are unknown. We derive a nonparametric estimator for the survival function when information regarding censoring frequency is available. ...
Gursoy, M.C.; Gezici, S. (2011)Cognitive radio transmissions in the presence of channel uncertainty are considered. In practical scenarios, cognitive secondary users need to perform both channel sensing in order to identify whether the channel is being ...