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
  • [21] Deep iterative residual back-projection networks for single-image super-resolution
    Tian, Chuan
    Hu, Jing
    Wu, Xi
    Wen, Wu
    JOURNAL OF ELECTRONIC IMAGING, 2022, 31 (02)
  • [22] Single Image Super-Resolution Using a Joint GMM Method
    Sandeep, Palakkattillam
    Jacob, Tony
    IEEE TRANSACTIONS ON IMAGE PROCESSING, 2016, 25 (09) : 4233 - 4244
  • [23] Robust Single-Image Super-Resolution Based on Adaptive Edge-Preserving Smoothing Regularization
    Huang, Shuying
    Sun, Jun
    Yang, Yong
    Fang, Yuming
    Lin, Pan
    Que, Yue
    IEEE TRANSACTIONS ON IMAGE PROCESSING, 2018, 27 (06) : 2650 - 2663
  • [24] Single-image super-resolution via a lightweight convolutional neural network with improved shuffle learning
    Lu, Xinbiao
    Xie, Xupeng
    Ye, Chunlin
    Xing, Hao
    Liu, Zecheng
    Chen, Yudan
    SIGNAL IMAGE AND VIDEO PROCESSING, 2024, 18 (01) : 233 - 241
  • [25] Deep Inception-Residual Laplacian Pyramid Networks for Accurate Single-Image Super-Resolution
    Tang, Yongliang
    Gong, Weiguo
    Chen, Xi
    Li, Weihong
    IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2020, 31 (05) : 1514 - 1528
  • [26] A Novel Solo Dictionary Learning Method for Single Image Super-resolution
    Dong, Rui
    Chen, Dongfang
    Wang, Xiaofeng
    PROCEEDINGS OF THE 2016 IEEE 11TH CONFERENCE ON INDUSTRIAL ELECTRONICS AND APPLICATIONS (ICIEA), 2016, : 1265 - 1269
  • [27] STRUCTURE PRESERVING SINGLE IMAGE SUPER-RESOLUTION
    Yang, Fan
    Xie, Don
    Jia, Huizhu
    Chen, Rui
    Xiang, Guoqing
    Gao, Wen
    2016 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP), 2016, : 1409 - 1413
  • [28] Survey of single image super-resolution reconstruction
    Li, Kai
    Yang, Shenghao
    Dong, Runting
    Wang, Xiaoying
    Huang, Jianqiang
    IET IMAGE PROCESSING, 2020, 14 (11) : 2273 - 2290
  • [29] Gradient boosting for single image super-resolution
    Xiong, Dongping
    Gui, Qiuling
    Hou, Wenguang
    Ding, Mingyue
    INFORMATION SCIENCES, 2018, 454 : 328 - 343
  • [30] Subspace Constraint for Single Image Super-Resolution
    Zhang, Yanlin
    Qin, Ding
    Gu, Xiaodong
    ARTIFICIAL NEURAL NETWORKS AND MACHINE LEARNING - ICANN 2021, PT III, 2021, 12893 : 395 - 407