New Method for Improving the Performance of SAR Image Segmentation: New Method for Improving the Performance of SAR Image Segmentation

Considering the shortage of edge preservation and low direction-resolution for SAR image segmentation based on the conventional wavelet transform domain, a new segmentation method is proposed based on Gray-Level Cooccurrence Probability (GLCP) features in the overcomplete Brushlet domain. This metho...

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Veröffentlicht in:Dian zi yu xin xi xue bao = Journal of electronics & information technology 2011-07, Vol.33 (7), p.1700-1705
Hauptverfasser: Yan, Xue-Ying, Jiao, Li-Cheng, Wang, Ling-Xia, Wan, Hong-Lin
Format: Artikel
Sprache:chi
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Zusammenfassung:Considering the shortage of edge preservation and low direction-resolution for SAR image segmentation based on the conventional wavelet transform domain, a new segmentation method is proposed based on Gray-Level Cooccurrence Probability (GLCP) features in the overcomplete Brushlet domain. This method compresses the redundant GLCP features extracted by the adaptive window Gabor filtering in different direction coefficient blocks using compressed sensing, then the Fuzzy C-Mean (FCM) clustering method is utilized to complete the clustering and obtain the segmentation result. The experiment results show that the new method has advantages in the edge preservation and direction extraction, and obtains better segmentation results with respect to other methods.
ISSN:1009-5896
DOI:10.3724/SP.J.1146.2010.01190