Improving Inverse Distance Weighting Method for Single-Image Super-Resolution

被引：0
|
作者：
Cumpim, Chaipichit [1 ]
Punchalard, Rachu [2 ]
Janchitrapongvej, Kanok [3 ]
Kimpan, Chom [4 ]
机构：
[1] Mahanakorn Univ Technol, Fac Engn, Elect Engn Grad Program, Bangkok 10530, Thailand
[2] Mahanakorn Univ Technol, Fac Engn, Dept Telecommun Engn, Bangkok 10530, Thailand
[3] Southeast Bangkok Coll, Fac Sci & Technol, Bangkok, Thailand
[4] Panyapiwat Inst Management, Fac Engn & Technol, Nonthaburi, Thailand
来源：
2016 13TH INTERNATIONAL CONFERENCE ON ELECTRICAL ENGINEERING/ELECTRONICS, COMPUTER, TELECOMMUNICATIONS AND INFORMATION TECHNOLOGY (ECTI-CON) | 2016年
关键词：
INTERPOLATION;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
This paper will be shown the problem and solve of the image interpolation by the directional inverse distance weighting (IDW). The anti-alias method which is the blurring kernel is used for solving on the IDW method. The problem of this method has occurred after this method is processed finish. The experiment results are shown the better performance than the conventional method.
引用
收藏
页数：5
相关论文
共 50 条
  • [31] SSR2: Sparse signal recovery for single-image super-resolution on faces with extreme low resolutions
    Abiantun, Ramzi
    Juefei-Xu, Felix
    Prabhu, Utsav
    Savvides, Marios
    PATTERN RECOGNITION, 2019, 90 : 308 - 324
  • [32] A high quality single-image super-resolution algorithm based on linear Bayesian MAP estimation with sparsity prior
    Sun, Dong
    Gao, Qingwei
    Lu, Yixiang
    Zheng, Lijun
    Wang, Hui
    DIGITAL SIGNAL PROCESSING, 2014, 35 : 45 - 52
  • [33] A Novel PDE-Based Single Image Super-Resolution Reconstruction Method
    Zhao, Xiaodong
    Cao, Jianzhong
    Zhou, Zuofeng
    Huang, Jijiang
    INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE, 2017, 31 (06)
  • [34] Single-image super-resolution via patch-based and group-based local smoothness modeling
    Mikaeli, Elhameh
    Aghagolzadeh, Ali
    Azghani, Masoumeh
    VISUAL COMPUTER, 2020, 36 (08) : 1573 - 1589
  • [35] A Unified Learning Framework for Single Image Super-Resolution
    Yu, Jifei
    Gao, Xinbo
    Tao, Dacheng
    Li, Xuelong
    Zhang, Kaibing
    IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2014, 25 (04) : 780 - 792
  • [36] Single Image Super-Resolution Based on Improved WGAN
    Yu, Lei
    Long, Xiang
    Tong, Chao
    PROCEEDINGS OF THE 2018 INTERNATIONAL CONFERENCE ON ADVANCED CONTROL, AUTOMATION AND ARTIFICIAL INTELLIGENCE (ACAAI 2018), 2018, 155 : 101 - 104
  • [37] Single image super-resolution by approximated Heaviside functions
    Deng, Liang-Jian
    Guo, Weihong
    Huang, Ting-Zhu
    INFORMATION SCIENCES, 2016, 348 : 107 - 123
  • [38] Neural component search for single image super-resolution?
    Mo, Lingfei
    Guan, Xuchen
    SIGNAL PROCESSING-IMAGE COMMUNICATION, 2022, 106
  • [39] A compendious study of super-resolution techniques by single image
    Pandey, Garima
    Ghanekar, Umesh
    OPTIK, 2018, 166 : 147 - 160
  • [40] Image Super-Resolution Method Based on Dual Learning
    Qiu, Zhao
    Zhuang, Chunyu
    Liu, Lihao
    Lin, Jiale
    Yuan, Sheng
    JOURNAL OF CIRCUITS SYSTEMS AND COMPUTERS, 2022, 31 (16)
12345