Single-Image Super-Resolution: A Survey

被引：7
|
作者：
Yao, Tingting [1 ]
Luo, Yu [1 ]
Chen, Yantong [1 ]
Yang, Dongqiao [1 ]
Zhao, Lei [2 ]
机构：
[1] Dalian Maritime Univ, Coll Informat Sci & Technol, Collaborat Innovat Res Inst Autonomous Ship, Dalian, Peoples R China
[2] Dalian Maritime Univ, Coll Environm Sci & Engn, Inst Environm Syst Biol, Dalian, Peoples R China
来源：
COMMUNICATIONS, SIGNAL PROCESSING, AND SYSTEMS, CSPS 2018, VOL II: SIGNAL PROCESSING | 2020年 / 516卷
基金：
中国国家自然科学基金;
关键词：
Single-image super-resolution; Learning-based; Deep learning; Survey;
D O I：
10.1007/978-981-13-6504-1_16
中图分类号：
TP31 [计算机软件];
学科分类号：
081202 ; 0835 ;
摘要：
Single-image super-resolution has been broadly applied in many fields such as military term, medical imaging, etc. In this paper, we mainly focus on the researches of recent years and classify them into non-deep learning SR algorithms and deep learning SR algorithms. For each classification, the basic concepts and algorithm processes are introduced. Furthermore, the paper discusses the advantages and disadvantages of different algorithms, which will offer potential research direction for the future development of SR.
引用
收藏
页码：119 / 125
页数：7
相关论文
共 50 条
  • [1] Single-Image Super-Resolution: A Benchmark
    Yang, Chih-Yuan
    Ma, Chao
    Yang, Ming-Hsuan
    [J]. COMPUTER VISION - ECCV 2014, PT IV, 2014, 8692 : 372 - 386
  • [2] A Systematic Survey of Deep Learning-Based Single-Image Super-Resolution
    Li, Juncheng
    Pei, Zehua
    Li, Wenjie
    Gao, Guangwei
    Wang, Longguang
    Wang, Yingqian
    Zeng, Tieyong
    [J]. ACM COMPUTING SURVEYS, 2024, 56 (10)
  • [3] A Content Dependent Kernel For Single-Image Super-Resolution
    Saryazdi, Saman
    Saryazdi, Saeid
    Nezanabadipour, Hossein
    [J]. 2013 5TH CONFERENCE ON INFORMATION AND KNOWLEDGE TECHNOLOGY (IKT), 2013, : 453 - 456
  • [4] EXTERNAL AND INTERNAL LEARNING FOR SINGLE-IMAGE SUPER-RESOLUTION
    Wang, Shuang
    Lin, Shaopeng
    Liang, Xuefeng
    Yue, Bo
    Jiao, Licheng
    [J]. 2015 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP), 2015, : 128 - 132
  • [5] Single-Image Super-Resolution Using Multihypothesis Prediction
    Chen, Chen
    Fowler, James E.
    [J]. 2012 CONFERENCE RECORD OF THE FORTY SIXTH ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS AND COMPUTERS (ASILOMAR), 2012, : 608 - 612
  • [6] Single-image super-resolution via local learning
    Yi Tang
    Pingkun Yan
    Yuan Yuan
    Xuelong Li
    [J]. International Journal of Machine Learning and Cybernetics, 2011, 2 : 15 - 23
  • [7] Rectified Binary Network for Single-Image Super-Resolution
    Xin, Jingwei
    Wang, Nannan
    Jiang, Xinrui
    Li, Jie
    Wang, Xiaoyu
    Gao, Xinbo
    [J]. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2024,
  • [8] PERCEPTUAL EVALUATION OF SINGLE-IMAGE SUPER-RESOLUTION RECONSTRUCTION
    Wang, Guangcheng
    Li, Leida
    Li, Qiaohong
    Gu, Ke
    Lu, Zhaolin
    Qian, Jiansheng
    [J]. 2017 24TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP), 2017, : 3145 - 3149
  • [9] Multilevel and Multiscale Network for Single-Image Super-Resolution
    Yang, Yong
    Zhang, Dongyang
    Huang, Shuying
    Wu, Jiajun
    [J]. IEEE SIGNAL PROCESSING LETTERS, 2019, 26 (12) : 1877 - 1881
  • [10] Collaborative Representation Cascade for Single-Image Super-Resolution
    Zhang, Yongbing
    Zhang, Yulun
    Zhang, Jian
    Xu, Dong
    Fu, Yun
    Wang, Yisen
    Ji, Xiangyang
    Dai, Qionghai
    [J]. IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2019, 49 (05): : 845 - 860
12345