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Markov Random Field Modeling in Image Analysis (Computer Science Workbench) 在线电子书 pdf 下载 txt下载 epub 下载 mobi 下载 2024

Markov Random Field Modeling in Image Analysis (Computer Science Workbench)
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简体网页||繁体网页
S. Z. Li 作者
Springer-Verlag Telos
译者
2001-07 出版日期
323 页数
USD 59.95 价格
Paperback
丛书系列
9784431703099 图书编码

Markov Random Field Modeling in Image Analysis (Computer Science Workbench) 在线电子书 图书标签: 我也是  小布的信息科学  MRF   

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发表于2024-11-23

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Markov Random Field Modeling in Image Analysis (Computer Science Workbench) 在线电子书 epub 下载 mobi 下载 pdf 下载 txt 下载 2024

Markov Random Field Modeling in Image Analysis (Computer Science Workbench) 在线电子书 epub 下载 mobi 下载 pdf 下载 txt 下载 2024

Markov Random Field Modeling in Image Analysis (Computer Science Workbench) 在线电子书 pdf 下载 txt下载 epub 下载 mobi 下载 2024


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Markov Random Field Modeling in Image Analysis (Computer Science Workbench) 在线电子书 图书描述

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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