Markov Random Fields for Vision and Image Processing (Hardcover)
暫譯: 視覺與影像處理的馬可夫隨機場

Andrew Blake, Pushmeet Kohli, Carsten Rother

  • 出版商: MIT
  • 出版日期: 2011-07-22
  • 售價: $1,830
  • 貴賓價: 9.8$1,793
  • 語言: 英文
  • 頁數: 472
  • 裝訂: Hardcover
  • ISBN: 0262015773
  • ISBN-13: 9780262015776
  • 相關分類: Machine LearningDeepLearning
  • 立即出貨 (庫存=1)

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商品描述

This volume demonstrates the power of the Markov random field (MRF) in vision, treating the MRF both as a tool for modeling image data and, utilizing recently developed algorithms, as a means of making inferences about images. These inferences concern underlying image and scene structure as well as solutions to such problems as image reconstruction, image segmentation, 3D vision, and object labeling. It offers key findings and state-of-the-art research on both algorithms and applications. After an introduction to the fundamental concepts used in MRFs, the book reviews some of the main algorithms for performing inference with MRFs; presents successful applications of MRFs, including segmentation, super-resolution, and image restoration, along with a comparison of various optimization methods; discusses advanced algorithmic topics; addresses limitations of the strong locality assumptions in the MRFs discussed in earlier chapters; and showcases applications that use MRFs in more complex ways, as components in bigger systems or with multiterm energy functions. The book will be an essential guide to current research on these powerful mathematical tools.

商品描述(中文翻譯)

本卷展示了馬可夫隨機場(Markov random field, MRF)在視覺中的強大功能,將MRF視為一種建模影像數據的工具,並利用最近開發的演算法作為對影像進行推斷的手段。這些推斷涉及潛在的影像和場景結構,以及解決影像重建、影像分割、3D視覺和物體標記等問題的方案。它提供了關於演算法和應用的關鍵發現和最先進的研究。在介紹MRF中使用的基本概念後,本書回顧了一些主要的MRF推斷演算法;展示了MRF的成功應用,包括分割、超解析度和影像修復,並比較了各種優化方法;討論了進階的演算法主題;針對早期章節中討論的MRF的強局部性假設的限制進行探討;並展示了以更複雜方式使用MRF的應用,作為更大系統中的組件或與多項能量函數結合使用。本書將成為當前這些強大數學工具研究的重要指南。