Context Aware Image Inpainting with Application to Virtual Restoration of Old Paintings

DOI

説明

In this paper, we explore how to use spatial context for image inpainting and we test it in two applications: photo-editing and crack removal in digitized old paintings. Context is determined based on the texture and color features. We use these contextual features to guide the search for image patches that can fill in the missing/damaged regions in a visually plausible way. A priori knowledge about spatial consistencies (similarities) among neighbouring image patches is encoded via a Markov Random Field (MRF) model. With this prior, the process of image inpainting is formulated as an optimization problem. We define an efficient inference engine as a valuable alternative to the so-called belief propagation methods. As a case study, we focus on crack removal from the Adoration of the Mystic Lamb (brothers Van Eyck, 1432), demonstrating potentials for virtual restoration of old paintings.

収録刊行物

  • IEICE Proceeding Series

    IEICE Proceeding Series 16 ENG-2-, 2013-07-20

    The Institute of Electronics, Information and Communication Engineers

キーワード

詳細情報 詳細情報について

  • CRID
    1390564227309466496
  • NII論文ID
    230000001694
  • DOI
    10.34385/proc.16.eng-2
  • ISSN
    21885079
  • 本文言語コード
    en
  • データソース種別
    • JaLC
    • CiNii Articles
  • 抄録ライセンスフラグ
    使用不可

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