Regularization for super-resolution image reconstruction

被引：0
|
作者：
Bannore, Vivek [1 ]
机构：
[1] Univ S Australia, Sch Elect & Informat Engn, Adelaide, SA, Australia
来源：
KNOWLEDGE-BASED INTELLIGENT INFORMATION AND ENGINEERING SYSTEMS, PT 2, PROCEEDINGS | 2006年 / 4252卷
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Super-resolution image reconstruction estimates a high-resolution image from a sequence of low-resolution, aliased images. The estimation is an inverse problem and is known to be ill-conditioned, in the sense that small errors in the observed images can cause large changes in the reconstruction. The paper discusses application of existing regularization techniques to super-resolution as an intelligent means of stabilizing the reconstruction process. Some most common approaches are reviewed and experimental results for iterative reconstruction are presented.
引用
收藏
页码：36 / 46
页数：11
相关论文
共 50 条
  • [31] Single-image super-resolution reconstruction using dark channel regularization network
    Di Zhang
    Jiazhong He
    Yun Zhao
    Huailing Zhang
    Signal, Image and Video Processing, 2021, 15 : 431 - 438
  • [32] Single image super-resolution reconstruction based on genetic algorithm and regularization prior model
    Li, Yangyang
    Wang, Yang
    Li, Yaxiao
    Jiao, Licheng
    Zhang, Xiangrong
    Stolkin, Rustam
    INFORMATION SCIENCES, 2016, 372 : 196 - 207
  • [33] Single-image super-resolution reconstruction using dark channel regularization network
    Zhang, Di
    He, Jiazhong
    Zhao, Yun
    Zhang, Huailing
    SIGNAL IMAGE AND VIDEO PROCESSING, 2021, 15 (02) : 431 - 438
  • [34] A MAP regularization super-resolution image reconstruction method based on improved immune algorithm
    Lei, Hong
    Han, Jianwen
    INFORMATION TECHNOLOGY AND INDUSTRIAL ENGINEERING, VOLS 1 & 2, 2014, : 129 - 136
  • [35] Research on non-local regularization model and algorithms for image super-resolution reconstruction
    Xiao L.
    Wei Z.-H.
    Jisuanji Xuebao/Chinese Journal of Computers, 2011, 34 (05): : 931 - 942
  • [36] Spatially Varying Regularization of Image Sequences Super-Resolution
    An, Yaozu
    Lu, Yao
    Zhai, Zhengang
    COMPUTER VISION - ACCV 2009, PT III, 2010, 5996 : 475 - 484
  • [37] Unified regularization framework for blind image super-resolution
    Chen, Yuanxu
    Luo, Yupin
    Hu, Dongcheng
    OPTICAL ENGINEERING, 2007, 46 (12)
  • [38] Image Super-resolution via adaptive filtering and regularization
    Ren, Jingbo
    Wu, Hao
    Dong, Weisheng
    Shi, Guangming
    OPTOELECTRONIC IMAGING AND MULTIMEDIA TECHNOLOGY III, 2014, 9273
  • [39] IMAGE PRIOR COMBINATION IN SUPER-RESOLUTION IMAGE RECONSTRUCTION
    Villena, Salvador
    Vega, Miguel
    Molina, Rafael
    Katsaggelos, Aggelos K.
    18TH EUROPEAN SIGNAL PROCESSING CONFERENCE (EUSIPCO-2010), 2010, : 616 - 620
  • [40] Research on Image Super-Resolution Reconstruction of Optical Image
    Jiang, Aiping
    Li, Xinwei
    Gao, Han
    COMMUNICATIONS, SIGNAL PROCESSING, AND SYSTEMS, CSPS 2018, VOL II: SIGNAL PROCESSING, 2020, 516 : 236 - 243
12345