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首页> 外文期刊>Arabian Journal for Science and Engineering >Image Inpainting Algorithm Based on Saliency Map and Gray Entropy
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Image Inpainting Algorithm Based on Saliency Map and Gray Entropy

机译：基于显着度图和灰度熵的图像修复算法

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摘要

Image inpainting algorithms based on separated priority are easily misled by image texture information, have poor accuracy in searching for matching patches with high priority and often result in inconsistent texture propagation and edge structure. Additionally, it is difficult to obtain the best-matching patch within a fixed range based on only color information. By considering the attention point of human vision and the statistical information of an image, an image inpainting algorithm based on saliency mapping and gray entropy is proposed. A saliency map is added to the priority stage, which ensures that the parts with strong structural information and visual importance are completed preferentially. The best-matching patch is determined by comprehensively considering the color information and saliency features. The search range of the matching patch is adaptively controlled based on gray entropy. Experiments concerning scratch damage, text removal and large area object removal are compared. The results of the proposed method have better visual effects and are superior in regard to the consistency of the edge structure and texture. The efficiency is similar to methods with a fixed local search range. The objective evaluation results also validate the performance of the proposed method.
机译：基于优先级分离的图像修复算法容易被图像纹理信息所误导，在搜索匹配的高优先级补丁时准确性较差，并且经常导致纹理传播和边缘结构不一致。另外，仅基于颜色信息很难在固定范围内获得最佳匹配的色标。结合人类视觉的关注点和图像的统计信息，提出了一种基于显着性映射和灰度熵的图像修复算法。显着性图被添加到优先级，以确保优先完成具有较强结构信息和视觉重要性的零件。最佳匹配的色块是通过综合考虑颜色信息和显着性特征来确定的。基于灰度熵来自适应地控制匹配补丁的搜索范围。比较了有关划痕损坏，文本删除和大面积对象删除的实验。所提出的方法的结果具有更好的视觉效果，并且在边缘结构和纹理的一致性方面优越。效率类似于具有固定本地搜索范围的方法。客观评估结果也验证了该方法的性能。

著录项

  • 来源
    《Arabian Journal for Science and Engineering》 |2019年第4期|3549-3558|共10页
  • 作者

    Zeng Jiexian; Fu Xiang; Leng Lu; Wang Can;

  • 作者单位

    Nanchang Hangkong Univ, Inst Comp Vis, Nanchang 330063, Jiangxi, Peoples R China;

    Nanchang Hangkong Univ, Inst Comp Vis, Nanchang 330063, Jiangxi, Peoples R China;

    Nanchang Hangkong Univ, Inst Comp Vis, Nanchang 330063, Jiangxi, Peoples R China;

    Nanchang Hangkong Univ, Inst Comp Vis, Nanchang 330063, Jiangxi, Peoples R China;

  • 收录信息 美国《科学引文索引》(SCI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Image inpainting; Saliency map; Gray entropy; Priority;

    机译：图像修补;显着图;灰度熵;优先级;

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