Image inpainting based on patch-oriented gradient energy

被引:0
|
作者
Zhang, Yitian [1 ]
Guan, Youjiang [2 ]
Wu, Yannan [1 ]
Sun, Feng [1 ]
Qin, Kaihuai [1 ]
机构
[1] Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China
[2] Department of Precision Instruments and Mechanology, Tsinghua University, Beijing 100084, China
关键词
Color matching - Image processing;
D O I
暂无
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
This paper presents a new exemplar-based image inpainting algorithm for image inpainting and object removal. A concept, called patch-oriented gradient energy, is introduced to estimate the color change of an image patch. By means of the maximum patch-oriented gradient energy among all the patches, the direction and strength of an edge in the patch can be estimated. Exemplar-based inpainting methods often contain three steps: the first is to compute the priority of each patch to be inpainted; the second is to match the patches; and the third is to update the global parameters such as unknown region's contour and the confidence values. Using the oriented gradient energy in the normal direction of the unknown region's contour, we firstly select the patches containing the strongest structure information (i.e., edge information). In the matching step, we compare not only the color values of the corresponding pixels, but also the edge information in the patches by the patch-oriented gradient energy. The experiments show that our algorithm can propagate the structures and textures near boundaries of the areas to be inpainted to the unknown regions in a correct way to obtain results with visually smooth edges in the inpainted image.
引用
收藏
页码:782 / 787
相关论文
共 50 条
  • [21] A novel patch matching algorithm for exemplar-based image inpainting
    Qian Fan
    Lifeng Zhang
    Multimedia Tools and Applications, 2018, 77 : 10807 - 10821
  • [22] A novel patch matching algorithm for exemplar-based image inpainting
    Fan, Qian
    Zhang, Lifeng
    MULTIMEDIA TOOLS AND APPLICATIONS, 2018, 77 (09) : 10807 - 10821
  • [23] An Improved Image Inpainting Method Based on Patch Matching and Texture Synthesis
    Lu, ShaoFang
    Han, ChangMing
    PROCEEDINGS OF THE 2019 31ST CHINESE CONTROL AND DECISION CONFERENCE (CCDC 2019), 2019, : 5933 - 5938
  • [24] An Intelligent Forensics Approach for Detecting Patch-Based Image Inpainting
    Wang, Xinyi
    Wang, He
    Niu, Shaozhang
    MATHEMATICAL PROBLEMS IN ENGINEERING, 2020, 2020
  • [25] Free gradient discontinuity and image inpainting
    Carriero M.
    Leaci A.
    Tomarelli F.
    Journal of Mathematical Sciences, 2012, 181 (6) : 805 - 819
  • [26] The Characteristics of Region Gradient for Image Inpainting
    Ye, Xueyi
    He, Wentao
    Chen, Huahua
    Li, Wangbing
    MULTIMEDIA AND SIGNAL PROCESSING, 2012, 346 : 129 - 136
  • [27] Patch Sparsity Based Image Inpainting Using Local Patch Statistics and Steering Kernel Descriptor
    Ghorai, Mrinmoy
    Mandal, Sekhar
    Chanda, Bhabatosh
    2016 23RD INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION (ICPR), 2016, : 781 - 786
  • [28] Deep Structured Energy-Based Image Inpainting
    Altinel, Fazil
    Ozay, Mete
    Okatani, Takayuki
    2018 24TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION (ICPR), 2018, : 423 - 428
  • [29] Scale-Invariant Image Inpainting Using Gradient-Based Image Composition
    Ghorai, Mrinmoy
    Samanta, Soumitra
    Chanda, Bhabatosh
    COMPUTER VISION, GRAPHICS, AND IMAGE PROCESSING, ICVGIP 2016, 2017, 10481 : 97 - 108
  • [30] Exemplar-based image inpainting using structure consistent patch matching
    Wang, Haixia
    Jiang, Li
    Liang, Ronghua
    Li, Xiao-Xin
    NEUROCOMPUTING, 2017, 269 : 90 - 96