Georgii L'Vovich Gimel'farb

Image Textures and Gibbs Random Fields

• Gebundenes Buch

Produktbeschreibung

This book presents novel 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. Audience: The book can be read by both specialists and graduate students in computer science and electrical engineering who take an interest in texture analysis and synthesis. Also, the book may be interesting to specialists and graduate students in applied mathematics who explore random fields.

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Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.

Produktdetails

• Verlag: Springer / Springer Netherland
• Seitenzahl: 268
• Erscheinungstermin: 30. September 1999
• Englisch
• Abmessung: 241mm x 160mm x 21mm
• Gewicht: 571g
• ISBN-13: 9780792359616
• ISBN-10: 0792359615
• Artikelnr.: 34950380

Inhaltsangabe

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.