一种改进的模糊聚类图像分割算法
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摘要
为了提高强噪声污染图像分割的鲁棒性,给出一种改进的非局部模糊聚类图像分割算法。改进算法将模糊因子的局部邻域值替换为非局部均值滤波图像的像素值,并加入局部空间信息,产生新的目标函数。借助拉格朗日乘子法,从最小化目标函数得出隶属度和聚类中心的迭代公式,进而完成图像分割。对合成图像、医学图像和自然图像添加高斯噪声、莱斯噪声和椒盐噪声,用于分割测试,结果显示,改进算法对强噪声图像具有更高的正确分割率和较小的模糊性。
The non-local fuzzy clustering image segmentation algorithm is revised to improve the robustness of image segmentation with strong noise pollution.The local neighborhood value of fuzzy factor is replaced by the pixel value of non-local mean filter image,and the local spatial information is introduced in fuzzy factor to generate a new objective function.With the help of Lagrange multiplier method,the iterative formulae of membership degree and clustering center are obtained from the optimal fuzzy clustering objective function,with which the image segmentation is completed.segmentation test on some synthetic images,medical images and natural images which are added Gauss noise,Rician noise and salt and pepper noise separately are experimented,and the results show that the revised algorithm is of higher correct segmentation rate and smaller ambiguity.
The non-local fuzzy clustering image segmentation algorithm is revised to improve the robustness of image segmentation with strong noise pollution.The local neighborhood value of fuzzy factor is replaced by the pixel value of non-local mean filter image,and the local spatial information is introduced in fuzzy factor to generate a new objective function.With the help of Lagrange multiplier method,the iterative formulae of membership degree and clustering center are obtained from the optimal fuzzy clustering objective function,with which the image segmentation is completed.segmentation test on some synthetic images,medical images and natural images which are added Gauss noise,Rician noise and salt and pepper noise separately are experimented,and the results show that the revised algorithm is of higher correct segmentation rate and smaller ambiguity.
引文
[1]BAI X Z,CHEN Z G,ZHANG Y,et al.Infrared ship target segmentation based on spatial information improved FCM[J/OL].IEEE Transactions on Cybernetics,2016,46(12):3259-3271[2017-03-05].http://dx.doi.org/10.1109/TCYB.2015.2501848.
[2]TIAN S R,WANG C,ZHANG H.A segmentation based global iterative censoring scheme for ship detection in synthetic aperture radar image.doc[C/OL]//Geoscience and Remote Sensing Symposium(IGARSS),2016IEEE International.Beijing:IEEE,2016:6513-6516[2017-03-05].http://dx.doi.org/10.1109/IGARSS.2016.7730702.
[3]GUZHVA O,ARDO H,HERLIN A,et al.Feasibility study for the implementation of an automatic system for the detection of social interactions in the waiting area of automatic milking stations by using a video surveillance system[J/OL].Computers and Electronics in Agriculture,2016,127(September 2016):506-509[2017-03-05].http://dx.doi.org/10.1016/j.compag.2016.07.010.
[4]RUHLMANN V,HEUSCH P,KUHL H,et al.Potential influence of Gadolinium contrast on image segmentation in MR-based attenuation correction with Dixon sequences in whole-body 18F-FDG PET/MR[J/OL].Magnetic Resonance Materials in Physics,Biology and Medicine,2016,29(2):301-308[2017-03-05].http://dx.doi.org/10.1007/s10334-015-0516-1.
[5]ZHAO F.Fuzzy clustering algorithms with self-tuning non-local spatial information for image segmentation[J/OL].Neurocomputing,2013,106(6):115-125[2017-03-05].http://dx.doi.org/10.1016/j.neucom.2012.10.022.
[6]NAYAK J,NAIK B,BEHERA H S.Fuzzy C-means(FCM)clustering algorithm:a decade review from2000to 2014[M/OL]//Computational Intelligence in Data Mining-Volume 2.New Delhi:Springer,2015:133-149[2017-03-05].http://dx.doi.org/10.1007/978-81-322-2208-8_14.
[7]LIAO L,LIN T,LI B.MRI brain image segmentation and bias field correction based on fast spatially constrained kernel clustering approach[J/OL].Pattern Recognition Letters,2008,29(10):1580-1588[2017-03-05].http://dx.doi.org/10.1016/j.patrec.2008.03.012.
[8]AHMED M N,YAMANY S M,MOHAMED N,et al.A modified fuzzy C-means algorithm for bias field estimation and segmentation of MRI data[J/OL].IEEE Transactions on Medical Imaging,2002,21(3):193-199[2017-03-05].http://dx.doi.org/10.1109/42.996338.
[9]CHEN S,ZHANG D.Robust image segmentation using FCM with spatial constraints based on new kernel-induced distance measure[J/OL].IEEE Transactions on Systems,Man,and Cybernetics,Part B(Cybernetics),2004,34(4):1907-1916[2017-03-05].http://dx.doi.org/10.1109/TSMCB.2004.831165.
[10]SZILAGYI L,BENYO Z,SZILAGYI S M,et al.MR brain image segmentation using an enhanced fuzzy Cmeans algorithm[C/OL]//Engineering in Medicine and Biology Society,2003.Proceedings of the 25th Annual International Conference of the IEEE.New York:IEEE,2003,1:724-726[2017-03-05].http://dx.doi.org/10.1109/IEMBS.2003.1279866.
[11]CAI W,CHEN S,ZHANG D.Fast and robust fuzzy C-means clustering algorithms incorporating local information for image segmentation[J/OL].Pattern Recognition,2007,40(3):825-838[2017-03-05].http://dx.doi.org/10.1016/j.patcog.2006.07.011.
[12]KRINIDIS S,CHATZIS V.A robust fuzzy local information C-means clustering algorithm[J/OL].IEEE Transactions on Image Processing,2010,19(5):1328-1337[2017-03-05].http://dx.doi.org/10.1109/TIP.2010.2040763.
[13]ZHAO F,JIAO L,LIU H.Fuzzy C-means clustering with non local spatial information for noisy image segmentation[J/OL].Frontiers of Computer Science in China,2011,5(1):45-56[2017-03-05].http://dx.doi.org/10.1007/s11704-010-0393-8.
[14]李琳,范九伦,赵凤.模糊C-均值聚类图像分割算法的一种改进[J/OL].西安邮电大学学报,2014,19(5):56-60[2017-03-05].http://dx.doi.org/10.13682/j.issn.2095-6533.2014.05.011.
[15]ZHANG X,SUN Y,WANG G,et al.Improved fuzzy clustering algorithm with non-local information for image segmentation[J/OL].Multimedia Tools and Applications,2017,76(6):7869-7895[2017-03-05].http://dx.doi.org/10.1007/s11042-016-3399-x.
[16]MA J,TIAN D,GONG M,et al.Fuzzy clustering with non-local information for image segmentation[J/OL].International Journal of Machine Learning and Cybernetics,2014,5(6):845-859[2017-03-05].http://dx.doi.org/10.1007/s13042-014-0227-3.
[17]BUADES A,COLL B,MOREL J M.A non-local algorithm for image denoising[C/OL]//Computer Vision and Pattern Recognition,2005.CVPR 2005.IEEE Computer Society Conference on.San Diego:IEEE,2005,2:60-65[2017-03-05].http://dx.doi.org/10.1109/CVPR.2005.38.
[18]BEZDEK J C.Cluster Validity with Fuzzy Sets[J/OL].Journal of Cybernetics,1973,3(3):58-73[2017-03-05].http://dx.doi.org/10.1080/01969727308546047.
[19]ADHIKARI S K,SING J K,BASU D K,et al.Conditional spatial fuzzy C-means clustering algorithm for segmentation of MRI images[J/OL].Applied Soft Computing,2015,34(September 2015):758-769[2017-03-05].http://dx.doi.org/10.1016/j.asoc.2015.05.038.
[20]GONG M,LIANG Y,SHI J,et al.Fuzzy C-means clustering with local information and kernel metric for image segmentation[J/OL].IEEE Transactions on Image Processing,2013,22(2):573-584[2017-03-05].http://dx.doi.org/10.1109/TIP.2012.2219547.
[21]JI Z X,SUN Q S,XIA D S.A modified possibilistic fuzzy C-means clustering algorithm for bias field estimation and segmentation of brain MR image[J/OL].Computerized Medical Imaging and Graphics,2011,35(5):383-397[2017-03-05].http://dx.doi.org/10.1016/j.compmedimag.2010.12.001.
[22]COCOSCO C A,KOLLOKIAN V,KWAN R K S,et al.BrainWeb:Online Interface to a 3D MRI Simulated Brain Database[J/OL].Neuroimage,1997(5):425[2017-03-05].http://brainweb.bic.mni.mcgill.ca/brainweb/.
[23]MathWorks Image Processing Toolbox,Natick,MA[Z/OL].[2017-03-05].http://cn.mathworks.com/matlabcentral/fileexchange/14237-rice-rician-distribution?requestedDomain=www.mathworks.com.
[2]TIAN S R,WANG C,ZHANG H.A segmentation based global iterative censoring scheme for ship detection in synthetic aperture radar image.doc[C/OL]//Geoscience and Remote Sensing Symposium(IGARSS),2016IEEE International.Beijing:IEEE,2016:6513-6516[2017-03-05].http://dx.doi.org/10.1109/IGARSS.2016.7730702.
[3]GUZHVA O,ARDO H,HERLIN A,et al.Feasibility study for the implementation of an automatic system for the detection of social interactions in the waiting area of automatic milking stations by using a video surveillance system[J/OL].Computers and Electronics in Agriculture,2016,127(September 2016):506-509[2017-03-05].http://dx.doi.org/10.1016/j.compag.2016.07.010.
[4]RUHLMANN V,HEUSCH P,KUHL H,et al.Potential influence of Gadolinium contrast on image segmentation in MR-based attenuation correction with Dixon sequences in whole-body 18F-FDG PET/MR[J/OL].Magnetic Resonance Materials in Physics,Biology and Medicine,2016,29(2):301-308[2017-03-05].http://dx.doi.org/10.1007/s10334-015-0516-1.
[5]ZHAO F.Fuzzy clustering algorithms with self-tuning non-local spatial information for image segmentation[J/OL].Neurocomputing,2013,106(6):115-125[2017-03-05].http://dx.doi.org/10.1016/j.neucom.2012.10.022.
[6]NAYAK J,NAIK B,BEHERA H S.Fuzzy C-means(FCM)clustering algorithm:a decade review from2000to 2014[M/OL]//Computational Intelligence in Data Mining-Volume 2.New Delhi:Springer,2015:133-149[2017-03-05].http://dx.doi.org/10.1007/978-81-322-2208-8_14.
[7]LIAO L,LIN T,LI B.MRI brain image segmentation and bias field correction based on fast spatially constrained kernel clustering approach[J/OL].Pattern Recognition Letters,2008,29(10):1580-1588[2017-03-05].http://dx.doi.org/10.1016/j.patrec.2008.03.012.
[8]AHMED M N,YAMANY S M,MOHAMED N,et al.A modified fuzzy C-means algorithm for bias field estimation and segmentation of MRI data[J/OL].IEEE Transactions on Medical Imaging,2002,21(3):193-199[2017-03-05].http://dx.doi.org/10.1109/42.996338.
[9]CHEN S,ZHANG D.Robust image segmentation using FCM with spatial constraints based on new kernel-induced distance measure[J/OL].IEEE Transactions on Systems,Man,and Cybernetics,Part B(Cybernetics),2004,34(4):1907-1916[2017-03-05].http://dx.doi.org/10.1109/TSMCB.2004.831165.
[10]SZILAGYI L,BENYO Z,SZILAGYI S M,et al.MR brain image segmentation using an enhanced fuzzy Cmeans algorithm[C/OL]//Engineering in Medicine and Biology Society,2003.Proceedings of the 25th Annual International Conference of the IEEE.New York:IEEE,2003,1:724-726[2017-03-05].http://dx.doi.org/10.1109/IEMBS.2003.1279866.
[11]CAI W,CHEN S,ZHANG D.Fast and robust fuzzy C-means clustering algorithms incorporating local information for image segmentation[J/OL].Pattern Recognition,2007,40(3):825-838[2017-03-05].http://dx.doi.org/10.1016/j.patcog.2006.07.011.
[12]KRINIDIS S,CHATZIS V.A robust fuzzy local information C-means clustering algorithm[J/OL].IEEE Transactions on Image Processing,2010,19(5):1328-1337[2017-03-05].http://dx.doi.org/10.1109/TIP.2010.2040763.
[13]ZHAO F,JIAO L,LIU H.Fuzzy C-means clustering with non local spatial information for noisy image segmentation[J/OL].Frontiers of Computer Science in China,2011,5(1):45-56[2017-03-05].http://dx.doi.org/10.1007/s11704-010-0393-8.
[14]李琳,范九伦,赵凤.模糊C-均值聚类图像分割算法的一种改进[J/OL].西安邮电大学学报,2014,19(5):56-60[2017-03-05].http://dx.doi.org/10.13682/j.issn.2095-6533.2014.05.011.
[15]ZHANG X,SUN Y,WANG G,et al.Improved fuzzy clustering algorithm with non-local information for image segmentation[J/OL].Multimedia Tools and Applications,2017,76(6):7869-7895[2017-03-05].http://dx.doi.org/10.1007/s11042-016-3399-x.
[16]MA J,TIAN D,GONG M,et al.Fuzzy clustering with non-local information for image segmentation[J/OL].International Journal of Machine Learning and Cybernetics,2014,5(6):845-859[2017-03-05].http://dx.doi.org/10.1007/s13042-014-0227-3.
[17]BUADES A,COLL B,MOREL J M.A non-local algorithm for image denoising[C/OL]//Computer Vision and Pattern Recognition,2005.CVPR 2005.IEEE Computer Society Conference on.San Diego:IEEE,2005,2:60-65[2017-03-05].http://dx.doi.org/10.1109/CVPR.2005.38.
[18]BEZDEK J C.Cluster Validity with Fuzzy Sets[J/OL].Journal of Cybernetics,1973,3(3):58-73[2017-03-05].http://dx.doi.org/10.1080/01969727308546047.
[19]ADHIKARI S K,SING J K,BASU D K,et al.Conditional spatial fuzzy C-means clustering algorithm for segmentation of MRI images[J/OL].Applied Soft Computing,2015,34(September 2015):758-769[2017-03-05].http://dx.doi.org/10.1016/j.asoc.2015.05.038.
[20]GONG M,LIANG Y,SHI J,et al.Fuzzy C-means clustering with local information and kernel metric for image segmentation[J/OL].IEEE Transactions on Image Processing,2013,22(2):573-584[2017-03-05].http://dx.doi.org/10.1109/TIP.2012.2219547.
[21]JI Z X,SUN Q S,XIA D S.A modified possibilistic fuzzy C-means clustering algorithm for bias field estimation and segmentation of brain MR image[J/OL].Computerized Medical Imaging and Graphics,2011,35(5):383-397[2017-03-05].http://dx.doi.org/10.1016/j.compmedimag.2010.12.001.
[22]COCOSCO C A,KOLLOKIAN V,KWAN R K S,et al.BrainWeb:Online Interface to a 3D MRI Simulated Brain Database[J/OL].Neuroimage,1997(5):425[2017-03-05].http://brainweb.bic.mni.mcgill.ca/brainweb/.
[23]MathWorks Image Processing Toolbox,Natick,MA[Z/OL].[2017-03-05].http://cn.mathworks.com/matlabcentral/fileexchange/14237-rice-rician-distribution?requestedDomain=www.mathworks.com.