Adaptive Fuzzy Clustering Algorithm with Local Information and Markov Random Field for Image Segmentation

Author(s):  
Jialiang Hu ◽  
Ying Wen
Author(s):  
GUO-YING LIU ◽  
AI-MIN WANG

In this study, a fuzzy clustering algorithm, MRHMRF-FCM, is proposed to capture and utilize the multiscale spatial constrains by employing multiresolution representations for the label image and the observed image in wavelet domain. In this algorithm, the inner-scale and inter-scale spatial constrains, respectively modeled by the hidden Markov random field models, serve as the penalization terms for the objective function of the FCM algorithm. On each scale, the improved objective function is optimized by taking advantage of Lagrange multipliers, and the final label of wavelet coefficient is determined by iteratively updating the membership degree and cluster centers. The experimental results on synthetic images, natural scenery color images and remote sensed images show that the proposed algorithm obtains much better segmentation results, such as accurately differentiating different regions and being immune to noise.


2016 ◽  
Vol 76 (6) ◽  
pp. 7869-7895 ◽  
Author(s):  
Xiaofeng Zhang ◽  
Yujuan Sun ◽  
Gang Wang ◽  
Qiang Guo ◽  
Caiming Zhang ◽  
...  

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