Image Textures and Gibbs Random Fields
Author:   Georgy L. Gimel'farb
Publisher:   Kluwer Academic Publishers
Volume:   v. 16
ISBN:  

9780792359616


Pages:   264
Publication Date:   30 September 1999
Format:   Hardback
Availability:   Awaiting stock   Availability explained
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Image Textures and Gibbs Random Fields


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Overview

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.

Full Product Details

Author:   Georgy L. Gimel'farb
Publisher:   Kluwer Academic Publishers
Imprint:   Kluwer Academic Publishers
Volume:   v. 16
ISBN:  

9780792359616


ISBN 10:   0792359615
Pages:   264
Publication Date:   30 September 1999
Audience:   College/higher education ,  Professional and scholarly ,  Postgraduate, Research & Scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   Awaiting stock   Availability explained
The supplier is currently out of stock of this item. It will be ordered for you and placed on backorder. Once it does come back in stock, we will ship it out for you.

Table of Contents

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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