An improved OSV cartoon-texture decomposition model

被引:1
|
作者
Xu, Jianlou [1 ]
Shang, Wanqing [1 ]
Guo, Yuying [1 ]
机构
[1] Henan Univ Sci & Technol, Sch Math & Stat, Luoyang 471023, Peoples R China
基金
中国国家自然科学基金;
关键词
Image decomposition; Cartoon texture; Alternating direction method; Bounded variation; TOTAL VARIATION MINIMIZATION; IMAGE DECOMPOSITION; BOUNDED VARIATION; RESTORATION; ALGORITHM;
D O I
10.1007/s11042-023-14521-y
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Cartoon-texture decomposition of images is a hot research topic in image processing, its main goal is to decompose a given image into cartoon and texture parts measured by different norms. In the existing partial decomposition model, the H-1 functional is often used to measure the oscillation function, which is obtained by the Hodge decomposition. Because a divergence-free vector function is neglected in the calculation of the Hodge decomposition, some directional information will be lost in the texture part, which will affect the decomposition results. In this paper, a new cartoon-texture decomposition model with divergence-free vector field constraint is established by analyzing the theory of the vector field. Mathematically, the new model makes the texture more accurate and complete. In order to solve this model, we transform the constrained optimization problem into an unconstrained problem by using the augmented Lagrange method, and then solve it with the alternating direction method. The proposed cartoon-texture decomposition model contains the divergence-free vector field information, so it improves the decomposition effect obviously, and the experimental results confirm the validity of the proposed model.
引用
收藏
页码:25761 / 25777
页数:17
相关论文
共 50 条
  • [1] An improved OSV cartoon-texture decomposition model
    Jianlou Xu
    Wanqing Shang
    Yuying Guo
    Multimedia Tools and Applications, 2023, 82 : 25761 - 25777
  • [2] A variational model for cartoon-texture decomposition of a color image
    Wang W.
    Wang J.
    Journal of Computational and Applied Mathematics, 2024, 449
  • [3] An Artistic Image Fusion Method with Improved Cartoon-Texture Decomposition
    Meng, Zhou
    ADVANCES IN MULTIMEDIA, 2022, 2022
  • [4] New perspectives on image compression using a cartoon-texture decomposition model
    Sprljan, N
    Izquierdo, E
    PROCEEDINGS EC-VIP-MC 2003, VOLS 1 AND 2, 2003, : 359 - 368
  • [5] A New TGV-Gabor Model for Cartoon-Texture Image Decomposition
    Liu, Xinwu
    IEEE SIGNAL PROCESSING LETTERS, 2018, 25 (08) : 1221 - 1225
  • [6] SIMULTANEOUS MULTIPHASE IMAGE SEGMENTATION AND CARTOON-TEXTURE DECOMPOSITION
    Chen, Hua-Zhu
    Wang, Wei-Wei
    Zhao, Chen-Ping
    Huang, Hua
    PROCEEDINGS OF 2016 INTERNATIONAL CONFERENCE ON WAVELET ANALYSIS AND PATTERN RECOGNITION (ICWAPR), 2016, : 230 - 235
  • [7] Cartoon-Texture decomposition with patch-wise decorrelation
    Li, Xiaofang
    Wang, Weiwei
    Feng, Xiangchu
    Qi, Tingting
    JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION, 2023, 90
  • [8] Cartoon-Texture Decomposition-Based Variational Pansharpening
    Chen, Yuerong
    Zhang, Mengliang
    Li, Song
    Wang, Zhongyuan
    Tian, Xin
    2020 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, 2020, : 2688 - 2692
  • [9] A NEW MULTIPLICATIVE NOISE REMOVAL MODEL COMBINING CARTOON-TEXTURE DECOMPOSITION METHOD
    Zhao, Chen-Ping
    Feng, Xiang-Chu
    Wang, Wei-Wei
    Ouyang, Zhao-Wei
    Chen, Hua-Zhu
    PROCEEDINGS OF 2016 INTERNATIONAL CONFERENCE ON WAVELET ANALYSIS AND PATTERN RECOGNITION (ICWAPR), 2016, : 49 - 54
  • [10] A Simultaneous Cartoon-Texture Image Segmentation and Image Decomposition Method
    LI Yafeng
    ZHAO Qijun
    ZHANG Wenbo
    FAN Pan
    ZHANG Renrui
    SUN Jieqi
    LI Jing
    Chinese Journal of Electronics, 2020, 29 (05) : 906 - 915