计算机应用研究2012，Vol.29Issue(7)：2737-2739,2746,4.DOI:10.3969/j.issn.1001-3695.2012.07.092
优选抑制式非局部空间模糊C-均值图像分割方法
Selection-suppressed non-local spatial FCM image segmentation method
摘要
Abstract
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.关键词
模糊C-均值聚类/图像分割/抑制式模糊C-均值/非局部空间信息Key words
fuzzy C-means clustering (FCM)/ image segmentation/ suppressed FCM (S-FCM)/ non-local spatial information分类
信息技术与安全科学引用本文复制引用
赵凤,范九伦..优选抑制式非局部空间模糊C-均值图像分割方法[J].计算机应用研究,2012,29(7):2737-2739,2746,4.基金项目
国家自然科学基金资助项目(61102095) （61102095）
陕西省自然科学基础研究计划资助项目(2012JQ8045) （2012JQ8045）
陕西省教育厅科研计划资助项目(11JK1008,2010JK835,2010JK837) （11JK1008,2010JK835,2010JK837）
