A spatial correlation based method for neighbor set selection in random field image models

Random field (RF) models have widespread application in image modeling and analysis. The effectiveness of these models is largely dependent on the choice of neighbor sets, which determine the spatial interactions that are represented by the model. We consider the problem of selecting these neighbor sets for simultaneous autoregressive and Gauss-Markov random field models, based on the correlation structure of the image to be modeled. A procedure for identifying appropriate neighbor sets is proposed, and experimental results which demonstrate the viability of this method are presented.

[1]  Alireza Khotanzad,et al.  A correlation structure based approach to neighborhood selection in random field models of texture images , 1994, Proceedings of 1st International Conference on Image Processing.

[2]  R. Kruse,et al.  Statistics with vague data , 1987 .

[3]  H. Akaike.  Maximum likelihood identification of Gaussian autoregressive moving average models , 1973 .

[4]  I. Duff,et al.  The state of the art in numerical analysis , 1997 .

[5]  J. Besag.  Spatial Interaction and the Statistical Analysis of Lattice Systems , 1974 .

[6]  John W. Woods,et al.  Two-dimensional Markov spectral estimation , 1976, IEEE Trans. Inf. Theory.

[7]  J. Rissanen,et al.  Modeling By Shortest Data Description* , 1978, Autom..

[8]  Rama Chellappa,et al.  Estimation and choice of neighbors in spatial-interaction models of images , 1983, IEEE Trans. Inf. Theory.

[9]  H. Akaike.  A new look at the statistical model identification , 1974 .

[10]  A. Kaufmann,et al.  Introduction to fuzzy arithmetic : theory and applications , 1986 .

[11]  A. Khotanzad,et al.  Feature selection for texture recognition based on image synthesis , 1987, IEEE Transactions on Systems, Man, and Cybernetics.

[12]  Alireza Khotanzad,et al.  Unsupervised Segmentation of Textured Images by Edge Detection in Multidimensional Feature , 1989, IEEE Trans. Pattern Anal. Mach. Intell..

[13]  Rama Chellappa,et al.  Classification of textures using Gaussian Markov random fields , 1985, IEEE Trans. Acoust. Speech Signal Process..

[14]  Jim Kalett.  People and crowds, a photographic album for artists and designers , 1978 .

[15]  G. Eichmann,et al.  Vector median filters , 1987 .

[16]  Béla Julesz,et al.  Visual Pattern Discrimination , 1962, IRE Trans. Inf. Theory.

[17]  Rama Chellappa,et al.  Texture synthesis and compression using Gaussian-Markov random field models , 1985, IEEE Transactions on Systems, Man, and Cybernetics.