Training dictionary by granular computing with L infinity-norm for patch granule-based image denoising

被引：0
|
作者：
Liu, Hongbing [1 ]
Liu, Gengyi [2 ]
Ma, Xuewen [1 ]
Liu, Daohua [1 ]
机构：
[1] Xinyang Normal Univ, Ctr Comp, Xinyang 464000, Peoples R China
[2] Xinyang Senior High Sch, Xinyang, Peoples R China
来源：
JOURNAL OF ALGORITHMS & COMPUTATIONAL TECHNOLOGY | 2018年 / 12卷 / 02期
关键词：
Granular computing; patch granule; image patch; image denoising; L infinity-norm;
D O I：
10.1177/1748301818761131
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
Considering the objects by different granularity reflects the recognition common law of people, granular computing embodies the transformation between different granularity spaces. We present the image denoising algorithm by using the dictionary trained by granular computing with L infinity-norm, which realizes three transformations, (1) the transformation from image space to patch granule space, (2) the transformation between granule spaces with different granularities, and (3) the transformation from patch granule space to image space. We demonstrate that the granular computing with L infinity-norm achieved the comparable peak signal to noise ratio (PSNR) measure compared with BM3D and patch group prior based denoising for eight natural images.
引用
收藏
页码：136 / 146
页数：11
相关论文
共 12 条
  • [1] Robust Estimation based Image Denoising With Patch based Dictionary
    Shanthi, P.
    Saravanakumar, S.
    2015 3RD INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING, COMMUNICATION AND NETWORKING (ICSCN), 2015,
  • [2] Principal component dictionary-based patch grouping for image denoising
    Yao, Shoukui
    Chang, Yi
    Qin, Xiaojuan
    Zhang, Yaozong
    Zhang, Tianxu
    JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION, 2018, 50 : 111 - 122
  • [3] Image Denoising via Patch-based L1-Norm Principal Component Analysis
    Ling, Xiao
    Brooks, J. Paul
    BIG DATA III: LEARNING, ANALYTICS, AND APPLICATIONS, 2021, 11730
  • [4] Patch-Based Image Denoising Model for Mixed Gaussian Impulse Noise Using L1 Norm
    Trivedi, Munesh C.
    Singh, Vikash Kumar
    Kolhe, Mohan L.
    Goyal, Puneet Kumar
    Shrimali, Manish
    INTELLIGENT COMMUNICATION AND COMPUTATIONAL TECHNOLOGIES, 2018, 19 : 77 - 84
  • [5] L1 Norm based Double-prior Learning for Image Denoising
    Du, Weinan
    Sun, Yanfeng
    Hu, Yongli
    2019 2ND INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND PATTERN RECOGNITION (AIPR 2019), 2019, : 93 - 96
  • [6] Double-Norm Constrained Image Denoising Algorithm Based on Dictionary Learning Sparsity and FCM Structure Clustering
    Ji, Changpeng
    He, Lina
    Dai, Wei
    IEEE ACCESS, 2022, 10 : 128304 - 128317
  • [7] RETRACTED: A method for remote sensing image denoising based on structured dictionary learning and cloud computing (Retracted Article)
    Yang, Ru
    Qin, Zhentao
    Zhao, Xiangyu
    INTERNATIONAL JOURNAL OF ELECTRICAL ENGINEERING EDUCATION, 2020,
  • [8] Dictionary learning-based denoising algorithm with expected patch log likelihood in diffusion-weighted magnetic resonance image
    Kim, Kyuseok
    Jeong, Hyun-Woo
    Lee, Youngjin
    JOURNAL OF THE KOREAN PHYSICAL SOCIETY, 2024, 85 (09) : 763 - 771
  • [9] Self-training dictionary based approximated l0 norm constraint reconstruction for compressed ECG
    Liu, Shengxing
    Wu, Fei-Yun
    BIOMEDICAL SIGNAL PROCESSING AND CONTROL, 2021, 68
  • [10] Infrared object detection via patch-tensor model and image denoising based on weighted truncated Schatten-p norm minimization
    Zhu, Yun
    Gong, Chengjian
    Liu, Shuwen
    Yu, Zhiyue
    Shao, Hanzeng
    Yu, Gaohang
    IET IMAGE PROCESSING, 2023, 17 (06) : 1762 - 1774
12