Aug. 2014

Article Contents

Chinese Optics> 2014> 7(4): 572-580.

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

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

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

doi:10.3788/CO.20140704.0572

College of Information Science and Technology, Beijing Normal University, Beijing 100875, China

Received Date:25 Feb 2014
Rev Recd Date:23 Apr 2014
Publish Date:25 Jul 2014

Abstract

Abstract

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.
- medical image de-noising,
- cerebrovascular,
- non-local means filter(NLM)

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References

[1] 王醒策,张美霞,武仲科,等. 基于全局 LBF 水平集模型的脑血管层次粗分割方法研究[J]. 光学精密工程,2013(12):3283-3296. WANG X C,ZHANG M X,WU ZH K,et al.. Level coarse brain vessel segmentation based on global LBF model[J].Opt. Precision Eng.,2013(12):3283-3296.(in Chinese)
[2] ANDREA C,PAOLO B,PIERO C,et al.. Local MRI analysis approach in diagnosis of early and prodromal Alzheimer's disease[J].NeuroImage,2011,58(2):469-480
[3] KHARE A,KHARE M,JEONG Y,et al.. Despeckling of medical ultrasound images using Daubechies complex wavelet transform[J].Signal Processing,2010,90(2):428-439.
[4] 刘希佳,陈宇,王文生,等. 小目标识别的小波阈值去噪方法[J]. 中国光学,2012,5(3):248-256. LIU X J,CHEN Y,WANG W SH,et al.. De-nosing algorithm of wavlet threshold for small target detection[J].Chinese Optics,2012,5(3):248-256.(in Chinese)
[5] DABOV K,FOI A,KATKOVNIK V,et al.. Image denoising by sparse 3-D transform-domain collaborative filtering[J].IEEE,2007,16(8):2080-2095.
[6] 王晟,张振荣,邵珺,等. 瞬态流场定量测量中平面诱导荧光图像的降噪[J]. 光学精密工程,2013,21(7):1858-1864. WANG SH,ZHANG ZH R,SHAO J,et al..Denoising of PLIF images for parameter measurement[J].Opt. Precision Eng.,2013,21(7):1858-1864.(in Chinese)
[7] PERONA P,MALIK J. Scale-space and edge detection using anisotropic diffusion[J].IEEE,1990,12(7):629-639.
[8] BUADES A,COLL B,MOREL J M. A non-local algorithm for image denoising[J].IEEE,2005,2:60-65.
[9] MANJ N J V,COUP P,BUADES A,et al.. New methods for MRI denoising based on sparseness and self-similarity[J].Medical Image Analysis,2012,16(1):18-27.
[10] KOENDERINK J J. The structure of images[J].Biological Cybernetics,1984,50(5):363-370.
[11] 余锦华,汪源源. 基于各向异性扩散的图像降噪算法综述[J]. 电子测量与仪器学报,2011,25(2):105-116. YU J H,WANG Y Y. Image noise reduction based on anisotropic diffusion:a survey[J].J. Electronic Measurement and Instrument,2011,25(2):105-116.(in Chinese)
[12] COUP P,YGER P,BARILLOT C.Fast Non Local Means Denoising for 3D MR Images[J].Lecture Notes in Computer Science,2006,4191:33-40.
[13] WANG J,GUO Y,YING Y,et al. Fast non-local algorithm for image denoising[R]. Proceedings of. 2006 IEEE International Conference on Image Processing,IEEE,Atlanta,USA,8-11 Oct. 2006:1429-1432.
[14] LI B,LIU Q S,XU J W,et al.. A new method for removing mixed noises[J].SCIENCE CHINA Information Sciences,2011,54(1):51-59.
[15] JIN Q,GRAMA I,LIU Q. Removing poisson noise by optimization of weights in non-local means[R]. Proceedings of 2012 Symposium on Photonics and Optoelectronics(SOPO),IEEE,Shanghai,China,21-23 May,2012:1-4.
[16] HU H,LI B,LIU Q. Non-local filter for removing a mixture of Gaussian and impulse noises[J].VISAPP,2012(1):145-150.