Selection-suppressed non-local spatial FCM image segmentation method
优选抑制式非局部空间模糊C-均值图像分割方法

When the image is heavily contaminated by noise, the adjacent pixels of a pixel may be also corrupted by noise. Under this condition, the local spatial information derived from the adjacent pixels of the giuen pixel cannot play a positive part in guiding noisy image segmentation. In order to solve this problem, this paper proposed a selection-suppressed non-local spatial FCM image segmentation method. This method firstly constructed the non-local weighted-sum image by using a set of pixels with a similar neighborhood configuration of the pixel in the image, and then performed a selection-suppressed FCM algorithm on the histogram of the obtained image. Segmentation experiments show that the proposed method further improves the robustness of FCM method to image noise and obtains more perfect image segmentation results.