A Robust Image Segmentation Algorithm Based on Weighted Filtering and Kernel Metric

被引:0
|
作者
Liu Yi [1 ]
Zhang Xiaofeng [1 ,2 ]
Sun Yujuan [1 ]
Wang Hua [1 ]
Zhang Caiming [3 ]
机构
[1] Ludong Univ, Sch Informat & Elect Engn, Yantai 264025, Shandong, Peoples R China
[2] Yantai Inst Technol, Sch Informat Engn, Yantai 264003, Shandong, Peoples R China
[3] Shandong Univ, Sch Software, Jinan 250014, Shandong, Peoples R China
关键词
image segmentation; fuzzy clustering; weighted filtering; kernel metric; pixel correlation; LOCAL INFORMATION; FUZZY; FCM;
D O I
10.3788/LOP231545
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Image segmentation is an important research direction in computer vision. Fuzzy clustering methods have been widely applied in image segmentation due to their unsupervised nature. However, traditional fuzzy clustering methods often fail to segment images with high-intensity noise and complex shapes. To solve this problem, a weighted factor is proposed based on saliency detection to construct a weighted filter and a pixel correlation model, which improves the noise resistance of the algorithm. The proposed weighted filter outperforms the optimal results of the traditional filter in terms of structural similarity by 0. 1. Moreover, a kernel metric is introduced to accommodate the segmentation needs of complex images. Extensive experimental results on synthetic, natural, remote sensing and medical images demonstrate that the proposed algorithm outperforms the traditional methods in visual effects and improves the segmentation accuracy by 2% compared with the optimal results of traditional methods.
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页数:13
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