[1]ZHANG Wei-wei,BO Hua,WANG Xiao-feng.SAR oil spill image segmentationbased on a multispectral clustering algorithm[J].CAAI Transactions on Intelligent Systems,2010,5(6):551-555.
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CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume:
5
Number of periods:
2010 6
Page number:
551-555
Column:
学术论文—机器感知与模式识别
Public date:
2010-12-25
- Title:
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SAR oil spill image segmentationbased on a multispectral clustering algorithm
- Author(s):
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ZHANG Wei-wei; BO Hua; WANG Xiao-feng
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School of Information Engineering, Shanghai Maritime University, Shanghai 200135, China
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- Keywords:
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synthetic aperture radar; graylevel cooccurrence matrices; spectral clustering; spill oil segmentation
- CLC:
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TP751
- DOI:
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- Abstract:
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The classic Kmean clustering algorithm is not suitable for the circumstances of arbitrary shapes and is prone to use the local minimum. In order to fix these shortcomings, a spectral clustering algorithm based on multitexture characteristics was proposed. The algorithm first used graylevel cooccurrence matrices (GLCM) to extract three features of the synthetic aperture radar (SAR) image and construct a characteristic matrix of spectral clustering. Next using the Ncut (Normalizedcut) criterion, it clustered the eigenvector corresponding to the second small eigenvalue of the Laplacian matrix in order to carry out the SAR oil spill image segmentation. Compared with the classic Kmean algorithm, the proposed method reduces the influence of coherent scattering noise on the segmentation result and efficiently conserves the edge of the image. The simulation results also show that the new method has a strong robustness for an image badly affected by the coherent scattering.