Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-1/W1, 339-344, 2013
https://doi.org/10.5194/isprsarchives-XL-1-W1-339-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
 
02 May 2013
DISCRETE TOPOLOGY BASED HIERARCHICAL SEGMENTATION FOR EFFICIENT OBJECT-BASED IMAGE ANALYIS: APPLICATION TO OBJECT DETECTION IN HIGH RESOLUTION SATELLITE IMAGES
A. H. Syed, E. Saber, and D. Messinger Chester F. Carlson Center for Imaging Science, Rochester Institute of Technology, Rochester, New York, 14623, USA
Department of Electrical and Microelectronic Engineering, Rochester Institute of Technology, Rochester, New York, 14623, USA
Keywords: Multi-scale, Scale-space, segmentation, High-resolution, topological information, contextual information, region merging, SCRM, OBIA, GEOBIA, object detection Abstract. With rapid developments in satellite and sensor technologies, there has been a dramatic increase in the availability of high resolution (HR) remotely sensed images. Hence, the ability to collect images remotely is expected to far exceed our capacity to analyse these images manually. Consequently, techniques that can handle large volumes of data are urgently needed. In many of today's multiscale techniques the underlying representation of objects is still pixel-based, i.e. object entities are still described/accessed via pixelbased descriptors, thereby creating a bottleneck when processing large volumes of data. Also, these techniques do not yet leverage the topological and contextual information present in the image. We propose a framework for Discrete Topology based hierarchical segmentation, addressing both the algorithms and data structures that will be required. The framework consists of three components: 1) Conversion to dart-based representation, 2) Size-Constrained-Region Merging to generate multiple segmentations, and 3) Update of two sparse arrays SIGMA and LAMBDA which together encode the topology of each region in the hierarchy. The results of our representation are demonstrated both on a synthetic and a real high resolution images. Application of this representation to objectdetection is also discussed.
Conference paper (PDF, 1380 KB)


Citation: Syed, A. H., Saber, E., and Messinger, D.: DISCRETE TOPOLOGY BASED HIERARCHICAL SEGMENTATION FOR EFFICIENT OBJECT-BASED IMAGE ANALYIS: APPLICATION TO OBJECT DETECTION IN HIGH RESOLUTION SATELLITE IMAGES, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-1/W1, 339-344, https://doi.org/10.5194/isprsarchives-XL-1-W1-339-2013, 2013.

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