Markov Random Field Modeling in Computer Vision

Released on by S.Z. Li
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  • Markov Random Field Modeling in Computer Vision Book Detail

  • Author : S.Z. Li
  • Release Date : 2012-12-06
  • Publisher : Springer Science & Business Media
  • Genre : Computers
  • Pages : 274
  • ISBN 13 : 4431669337
  • File Size : 20,20 MB
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Markov Random Field Modeling in Computer Vision by S.Z. Li PDF Summary

Book Description: Markov random field (MRF) modeling provides a basis for the characterization of contextual constraints on visual interpretation and enables us to develop optimal vision algorithms systematically based on sound principles. This book presents a comprehensive study on using MRFs to solve computer vision problems, covering the following parts essential to the subject: introduction to fundamental theories, formulations of various vision models in the MRF framework, MRF parameter estimation, and optimization algorithms. Various MRF vision models are presented in a unified form, including image restoration and reconstruction, edge and region segmentation, texture, stereo and motion, object matching and recognition, and pose estimation. This book is an excellent reference for researchers working in computer vision, image processing, pattern recognition and applications of MRFs. It is also suitable as a text for advanced courses in the subject.

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Markov Random Fields

File Size : 91,91 MB
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Introduces the theory and application of Markov random fields in image processing/computer vision. Modelling images through the local interaction of Markov mode

Stochastic Image Processing

Stochastic Image Processing

File Size : 17,17 MB
Total View : 8304 Views
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Stochastic Image Processing provides the first thorough treatment of Markov and hidden Markov random fields and their application to image processing. Although