Image textures and Gibbs random fields

書誌事項

Image textures and Gibbs random fields

by Georgy L. Gimel'farb

(Computational imaging and vision, v. 16)

Kluwer Academic Publishers, c1999

この図書・雑誌をさがす

注記

Bibliographical reference: p. 243-248

Includes index

内容説明・目次

内容説明

This text presents techniques for describing image textures. Contrary to the usual practice of embedding the images to known modelling frameworks borrowed from statistical physics or other domains, this book deduces the Gibbs models from basic image features and tailors the modelling framework to the images. This approach results in more general Gibbs models than can be either Markovian or non-Markovian and possess arbitrary interaction structures and strengths. The book presents computationally feasible algorithms for parameter estimation and image simulation and demonstrates their abilities and limitations by numerous experimental results. The book avoids too abstract mathematical constructions and gives explicit image-based explanations of all the notions involved.

目次

Preface. Acknowledgements. Instead of introduction. 1. Texture, Structure, and Pairwise Interactions. 2. Markov and Non-Markov Gibbs Image Models. 3. Supervised MLE-Based Parameter Learning. 4. Supervised Conditional MLE-Based Learning. 5. Experiments in Simulating Natural Textures. 6. Experiments in Retrieving Natural Textures. 7. Experiments in Segmenting Natural Textures. Texture Modelling: Theory vs. Heuristics. References. Index.

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