期刊文献+
任意字段
题名或关键词
题名
关键词
文摘
作者
第一作者
机构
刊名
分类号
参考文献
作者简介
基金资助
栏目信息

图像分割中的马尔可夫随机场方法综述 被引量：65

A Survey of the Markov Random Field Method for Image Segmentation
在线阅读 下载PDF
导出
摘要 马尔可夫随机场方法是图像分割中一个极为活跃的研究方向。本文介绍了基于马尔可夫随机场模型的一般理论与图像的关系,给出它在图像分割中的通用框架:包括空域和小波域图像模型的建立、最优准则的选取、标号数的确定、图像模型参数的估计和图像分割的实现,评述了其在图像分割中的应用,展望其发展的方向。 Markov random field method is a very active research field in image segmentation. This paper introduces the relationship between a general theory based on Markov random field method and the images, and provides a general framework in image segmentation, including the construction of spatial and wavelet domain image models, the selection of the optimization criterion, calculation of the number of labeling, parameter estimation of image models and the realization of image segmentation. The applications of image segmentation are reviewed. And a few possible trends are discussed.
作者 李旭超 朱善安
机构地区 浙江大学电气工程学院
出处 《中国图象图形学报》 CSCD 北大核心 2007年第5期789-798,共10页 Journal of Image and Graphics
关键词 马尔可夫随机场 图像分割 贝叶斯准则 参数估计 markov random field, image segmentation, bayesian principle, parameter estimation
分类号 TP391 [自动化与计算机技术—计算机应用技术]
  • 相关文献

参考文献50

  • 1Lei T,Sewchand W.Statistical approach to X-ray CT imaging and its applications in image analysis-Part 2:A new stochastic model-based image segmentation technique for X-ray CT images[J].IEEE Transactions on Medical Image,1992,11(1):62 ～69.
  • 2Zhang J,Modestino J W.A model-fitting approach to cluster validity with application to stochastic model-based image segmentation[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,1990,12(10):1009 ～ 1017.
  • 3Zheng R L,MacFall J R,Harrington D P.Parameter estimation and tissue segmentation from multispectral MR images[J].IEEE Transactions on Medical Image,1994,13(3):441 ～449.
  • 4Besag J.On the statistical analysis of dirty data[J].Journal of the Royal Statistical Society,1986,48(3):259 ～302.
  • 5Bouman C,Liu B.Multiple resolution segmentation of texture images[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,1991,13(2):99 ～ 113.
  • 6Geman S,Geman D.Stochsstic relaxation,Gibbs distributions and the Bayesian restoration of images[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,1984,6(6):721 ～741.
  • 7Besag J.Spatial interaction and the statistical analysis of lattice systems[J].Journal of the Royal Statistical Society,1974,36 (2):192 ～ 236.
  • 8Chen Xilin,Gao Wen,Zhang Jing.Motion analysis with stochastic approach[A].In:Proceedings of 3rd International Conference on Auto.Robotics and Computer Vision[C],Nangang,SINGAPORE,1994,3:1709 ～1713.
  • 9Li S Z.Markov Random Field Modeling in Computer Vision[M].Tokyo,Japan:Springer-Verlag,1995.
  • 10Gerhard Winkler.Image Analysis,Random Fields and Dynamic Monte Carlo Methods[M].Berlin Germany:Springer-Verlag,1995.

二级参考文献22

  • 1王勇,吴立德.图象恢复和边缘提取的后验均值方法[J].电子学报,1994,22(2):70-75. 被引量：6
  • 2[1]Tulkel Derin, et al., Modeling and segmentation of noisy and textured images using Gibbs random fields, IEEE Trans. on PAMI., 1987, PAMI-9(1), 39-55.
  • 3[2]T.N. Pappas, An adaptive clustering algorithm for image segmentation, IEEE Trans. on Signal Processing, 1992, SP-40(4), 901-913.
  • 4[3]S.Z. Li, Markov Random Field Modeling in Computer Vision, Tokyo, Springer-Verlag, 1995.
  • 5[4]Y.Y. Zhang, et al., Segmentation of Brain MR images through a hidden Markov random field model and the expectation maximization algorithm, IEEE Trans. on Medical Imaging, 2001,MI-20(1), 15-22.
  • 6Zhuang X，IEEE Trans Image Processing，1996年，5卷，9期，1293页
  • 7Zhuang X，IEEE Trans Pattern Anal Machine Intell，1992年，14卷，1期，19页
  • 8Hyeokho Choi,Richard Baraniuk.Multiscale document segmentation using wavelet-do main hidden markov models [A].in Proc.IST/SPIE's 12th Annual Internation al Symposium Electronic Imaging 2000,Science & Technology [C].San Jose,CA:200 0.
  • 9M S Crouse,R G Baraniuk.Wavelet-based statistical signal processing using Hidde n Markov models [J].IEEE Trans.Signal Proc.1998,46:886-902.
  • 10H Choi,R G Baraniuk.Image segmentation using wavelet-domain classification [J ].Proceedings of SPIE technical conference on Mathematical Modeling,Bayesian Es timation and Inverse problems,1999,3816:306-320.

共引文献41

同被引文献817

引证文献65

二级引证文献385

中国图象图形学报
2007年 第5期

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部