Without considering the spatial information of images, the original fuzzy C-means algorithm is very sensitive to image noise.
由于原始的模糊c -均值聚类算法没有考虑图像的空间信息，算法对图像中的噪音点十分敏感。
The traditional way is to obtain the sub-image by sampling the noised image in spatial or frequency domain, then calculate its variance to replace that of the original noise.
传统方法是通过空域或频域采样，得到该子噪声图像，然后直接对其估计方差，它对图像信息的分布有要求。
The traditional way is to obtain the sub-image by sampling the noised image in spatial or frequency domain, then calculate its variance to replace that of the original noise.
传统方法是通过空域或频域采样，得到该子噪声图像，然后直接对其估计方差，它对图像信息的分布有要求。
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