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中文摘要：
为克服传统谱聚类算法应用到含噪图像分割时易受到图像中噪声影响的问题，提出一种基于空间特征的谱聚类含噪图像分割算法．该方法利用图像各个像素的灰度信息、局部空间邻接信息及非局部空间信息设计像素的三维特征，通过引入空间紧致性函数建立像素特征点与其K个最近邻之间的相似性，进而利用谱聚类算法得到图像的最终分割结果．实验中采用含噪的人工图像、自然图像及合成孔径雷达图像与空间模糊聚类、规范切谱聚类和Nystrom方法3种算法进行对比实验，实验结果验证文中方法能克服图像中噪声影响并取得较满意的分割效果．
英文摘要：
To overcome the problem that the traditional spectral clustering is easily influenced by image noise while applied to noisy image segmentation, a space feature based spectral clustering algorithm for noise image segmentation is proposed. In this method, gray value, local spatial information and non-local spatial information of each pixel are utilized to construct a 3-dimensional feature dataset. Then, the space compactness function is introduced to compute the similarity between each feature point and its K nearest neighbors. Finally, the final image segmentation result is obtained by spectral clustering algorithm. Some noisy artificial images, nature images and synthetic aperture radar images are utilized and normalized. Cut, FCM_s and Nystrom method are compared with the proposed method in the experiments. The experimental results show that the proposed method is robustness and obtains the satisfying segmentation result.
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