Volume 7 Issue 4
Aug.  2014
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CHEN Xing, SONG Zhi-yang, ZHOU Ming-quan, WU Zhong-ke, WANG Xing-ce. An improved non-local mean filter filtering algorithm facing the cerebrovascular segmentation[J]. Chinese Optics, 2014, 7(4): 572-580. doi: 10.3788/CO.20140704.0572
Citation: CHEN Xing, SONG Zhi-yang, ZHOU Ming-quan, WU Zhong-ke, WANG Xing-ce. An improved non-local mean filter filtering algorithm facing the cerebrovascular segmentation[J]. Chinese Optics, 2014, 7(4): 572-580. doi: 10.3788/CO.20140704.0572

An improved non-local mean filter filtering algorithm facing the cerebrovascular segmentation

doi: 10.3788/CO.20140704.0572
  • Received Date: 25 Feb 2014
  • Rev Recd Date: 23 Apr 2014
  • Publish Date: 25 Jul 2014
  • We introduce the classical non-local means filtering algorithm and the improved non-local means filtering algorithm with the weight function modified by Manjn. In this paper, we propose different weight function, and make it have rotating shift invariance for the local windows while keeping the time complexity of optimizing the visual effect and SNR. By adding noise standard deviation from Gaussian additive noise ranging from 10 to 100, we compare the improved algorithms with traditional filtering algorithms and Manjn non-mean filtering algorithm. The results show that the improved algorithm from either visual or numerical is superior to Manjn non-mean filtering algorithm.

     

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