Segmentation of polarimetric SAR data using contour information via spectral graph partitioning

TitleSegmentation of polarimetric SAR data using contour information via spectral graph partitioning
Publication TypeConference Paper
Year of Publication2007
AuthorsErsahin, K., I. G. Cumming, and R. K. Ward
Conference NameGeoscience and Remote Sensing Symposium, 2007. IGARSS 2007. IEEE International
Pagination2240 -2243
Date Publishedjul.
Keywordscontour information, global optimal solution, image segmentation, multiclass spectral clustering, pattern clustering, polarimetric SAR data, POLSAR data, radar polarimetry, spectral graph partitioning, synthetic aperture radar

A new method for segmenting polarimetric Synthetic Aperture Radar (POLSAR) data is proposed. Image segmentation is formulated as a graph partitioning problem. Spectral graph partitioning - known to provide perceptually plausible image segmentation results using one or more cues (e.g., similarity, proximity, contour continuity) - is applied on POLSAR image data. The degree of similarities between pairs of pixels are calculated based on contour information. Graph partitioning is performed using the Multiclass Spectral Clustering method that minimizes the normalized cut cost function to ensure minimal similarity between partitions. The resulting segmentation is an approximation to the global optimal solution. C-band POLSAR data acquired by CV-580 are used for testing the performance. The results are found to closely agree with manual segmentations.


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