26 March 1986 Segmentation And Global Parameter Estimation Of Textured Images Modelled By Markov Random Fields
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Proceedings Volume 0635, Applications of Artificial Intelligence III; (1986) https://doi.org/10.1117/12.964150
Event: 1986 Technical Symposium Southeast, 1986, Orlando, United States
This paper is concerned with identifying and estimating the parameters of the different texture regions that comprise a textured image. A textured region here is modelled by a Markov Random Field (MRF). The MRF is parametrized by a parameter vector α , ana has a noncausal structure. We assume no a prior knowledge about the different texture regions, their associated texture parameters, or the available number of textured regions. The image is partitioned into disjoint square windows and a maximum likelihood estimate (MLE) (or a sufficient statistis) α* for α (for a fixed order model) is obtained in each window. The components of α* are viewed as features, and a as a feature vector. The windows are grouped in different texture regions based on feature selection and clustering analysis of the α* vectors in the different windows. To simplify the clustering process, the dimensionality of the feature vector is reduced via a Karhunen-Loeve decomposition of the between-to-within scatter matrix of the α* vectors. Each α* is projected onto the dominant mode (eigenvector) of the scatter matrix. The projected data is used in the clustering process. The clustering is achieved by minimizing a within group variance criterion which has been weighted by a factor that explicitly depends on the number of groups. To reduce the computational cost associated with this method, it is accompanied by a "valley method". Finally, by exploiting the asymptotic normality of the MLE, we compute the tglobal MLE α* for each textured region by properly combining the locally estimated MLE α* in the various windows that comprise the region. The global MLE α* for a region is notning but an appropriately weighted linear combination of the local MLE set {αk*}.
© (1986) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Fernand S. Cohen, Fernand S. Cohen, Zhigang Fan, Zhigang Fan, "Segmentation And Global Parameter Estimation Of Textured Images Modelled By Markov Random Fields", Proc. SPIE 0635, Applications of Artificial Intelligence III, (26 March 1986); doi: 10.1117/12.964150; https://doi.org/10.1117/12.964150

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