Markov Random Field Modeling in Image Analysis

To chci

Markov random field (MRF) theory provides a basis for modeling contextual constraints in visual processing and interpretation. It enables systematic development of optimal vision algorithms when used with optimization principles. This detailed and thoroughly enhanced third edition presents a comprehensive study / reference to theories, methodologies and recent developments in solving computer vision problems based on MRFs, statistics and optimization. It treats various problems in low- and high-level computational vision in a systematic and unified way within the MAP-MRF framework. Among the main issues covered are: how to use MRFs to encode contextual constraints that are indispensable to image understanding; how to derive the objective function for the optimal solution to a problem; and how to design computational algorithms for finding an optimal solution.- … celý popis

Podrobná bibliografie

Hlavní autor

Stan Z Li

Další autoři

SpringerLink (online služba)

Typ dokumentu

Knihy

Fyzický popis

1 online zdroj (XXII, 362 p. 111 illus.)

Vydáno

London : Springer London : 2009

Vydání

3rd ed. 2009

Edice

Advances in Computer Vision and Pattern Recognition,

Témata

elektronické knihy

ISBN

978-1-84800-279-1

Obsah

Mathematical MRF Models -- Low-Level MRF Models -- High-Level MRF Models -- Discontinuities in MRF#x0027;s -- MRF Model with Robust Statistics -- MRF Parameter Estimation -- Parameter Estimation in Optimal Object Recognition -- Minimization - Local Methods -- Minimization - Global Methods