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Image Inpainting Algorithm Based on Low-Rank Approximation and Texture Direction

机译:基于低秩逼近和纹理方向的图像修复算法

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摘要

Existing image inpainting algorithm based on low-rankmatrix approximation cannot be suitable for complex, large-scale, damaged texture image. An inpainting algorithm based on low-rank approximation and texture direction is proposed in the paper. At first, we decompose the image using low-rank approximationmethod. Then the area to be repaired is interpolated by level set algorithm, and we can reconstruct a new image by the boundary values of level set. In order to obtain a better restoration effect, we make iteration for low-rank decomposition and level set interpolation. Taking into account the impact of texture direction, we segment the texture andmake low-rank decomposition at texture direction. Experimental results show that the new algorithmis suitable for texture recovery and maintaining the overall consistency of the structure, which can be used to repair large-scale damaged image.
机译:现有的基于低秩矩阵逼近的图像修复算法不适用于复杂,大规模,受损的纹理图像。提出了一种基于低秩逼近和纹理方向的修复算法。首先,我们使用低秩逼近方法分解图像。然后通过水平集算法对要修复的区域进行插值,然后我们可以通过水平集的边界值来重建新图像。为了获得更好的恢复效果,我们对低秩分解和水平集插值进行迭代。考虑到纹理方向的影响,我们对纹理进行分割,并在纹理方向进行低等级分解。实验结果表明,该算法适用于纹理恢复并保持结构的整体一致性,可用于修复大范围的损伤图像。

著录项

  • 来源
    《Mathematical Problems in Engineering》 |2014年第21期|621520.1-621520.11|共11页
  • 作者

    Li Jinjiang; Li Mengjun; Fan Hui;

  • 作者单位

    Tsinghua Univ, Dept Comp Sci & Technol, Beijing 100084, Peoples R China.;

    Shandong Inst Business & Technol, Sch Comp Sci & Technol, Yantai 264005, Peoples R China.;

    Shandong Inst Business & Technol, Sch Comp Sci & Technol, Yantai 264005, Peoples R China.;

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