针对偏置环境下图像分割问题，提出了一种基于偏置场估计的模糊聚类算法。
A novel FCM segmentation algorithm is proposed based on bias field estimation with respect to the segmentation issue of defocused images with illumination patterns under bias field.
论文提出了基于RBF神经网络图像分割参数估计的方法。
In this paper, we present a method of estimation of image segmentation parameters based on RBF neural network.
借助于图像运动的变阶参数模型和鲁棒回归分析，提出一种基于运动分割的图像运动估计方法。
A motion based segmentation scheme for image motion estimation is proposed using variable order parameterized models of image motion and robust regression.
最后根据SAR图像的统计性质，利用基于混合模型估计的分类后验概率将初始分割结果逐尺度进行细化得到SAR图像的最终分割。
Third, the initial segmentation is refined scale by scale to get the final segmentation of the SAR image based on the posterior probability of classification which is estimated by the mixture model.
最后根据SAR图像的统计性质，利用基于混合模型估计的分类后验概率将初始分割结果逐尺度进行细化得到SAR图像的最终分割。
Third, the initial segmentation is refined scale by scale to get the final segmentation of the SAR image based on the posterior probability of classification which is estimated by the mixture model.
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