Markov Random Field Modeling in Image Analysis (Computer Science Workbench)

Markov Random Field Modeling in Image Analysis (Computer Science Workbench) pdf epub mobi txt 电子书 下载 2025

出版者:Springer-Verlag Telos
作者:S. Z. Li
出品人:
页数:323
译者:
出版时间:2001-07
价格:USD 59.95
装帧:Paperback
isbn号码:9784431703099
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  • 我也是 
  • 小布的信息科学 
  • MRF 
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Markov random field (MRF) theory provides a basis for modeling contextual constraints in visual processing and interpretation. It enables us to develop optimal vision algorithms systematically when used with optimization principles. This book presents a comprehensive study on the use of MRFs for solving computer vision problems. The book covers the following parts essential to the subject: introduction to fundamental theories, formulations of MRF vision models, MRF parameter estimation, and optimization algorithms. Various vision models are presented in a unified framework, including image restoration and reconstruction, edge and region segmentation, texture, stereo and motion, object matching and recognition, and pose estimation. This second edition includes the most important progress in Markov modeling in image analysis in recent years such as Markov modeling of images with "macro" patterns (e.g. the FRAME model), Markov chain Monte Carlo (MCMC) methods, reversible jump MCMC. This book is an excellent reference for researchers working in computer vision, image processing, statistical pattern recognition and applications of MRFs. It is also suitable as a text for advanced courses in these areas.

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